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  • 251.
    Markström, Johannes
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska högskolan.
    3D Position Estimation of a Person of Interest in Multiple Video Sequences: People Detection2013Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    In most cases today when a specific person's whereabouts is monitored through video surveillance it is done manually and his or her location when not seen is based on assumptions on how fast he or she can move. Since humans are good at recognizing people this can be done accurately, given good video data, but the time needed to go through all data is extensive and therefore expensive. Because of the rapid technical development computers are getting cheaper to use and therefore more interesting to use for tedious work.

    This thesis is a part of a larger project that aims to see to what extent it is possible to estimate a person of interest's time dependent 3D position, when seen in surveillance videos. The surveillance videos are recorded with non overlapping monocular cameras. Furthermore the project aims to see if the person of interest's movement, when position data is unavailable, could be predicted. The outcome of the project is a software capable of following a person of interest's movement with an error estimate visualized as an area indicating where the person of interest might be at a specific time.

    This thesis main focus is to implement and evaluate a people detector meant to be used in the project, reduce noise in position measurement, predict the position when the person of interest's location is unknown, and to evaluate the complete project.

    The project combines known methods in computer vision and signal processing and the outcome is a software that can be used on a normal PC running on a Windows operating system. The software implemented in the thesis use a Hough transform based people detector and a Kalman filter for one step ahead prediction. The detector is evaluated with known methods such as Miss-rate vs. False Positives per Window or Image (FPPW and FPPI respectively) and Recall vs. 1-Precision.

    The results indicate that it is possible to estimate a person of interest's 3D position with single monocular cameras. It is also possible to follow the movement, to some extent, were position data are unavailable. However the software needs more work in order to be robust enough to handle the diversity that may appear in different environments and to handle large scale sensor networks.

  • 252.
    Markus, Nenad
    et al.
    Faculty of Electrical Engineering and Computing, University of Zagreb.
    Gogic, Ivan
    Faculty of Electrical Engineering and Computing, University of Zagreb.
    Pandžic, Igor
    Faculty of Electrical Engineering and Computing, University of Zagreb.
    Ahlberg, Jörgen
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Memory-efficient Global Refinement of Decision-Tree Ensembles and its Application to Face Alignment2018Ingår i: Proceedings of BMVC 2018 and Workshops, Newcastle upon Tyne, UK: The British Machine Vision Association and Society for Pattern Recognition , 2018, s. 1-11, artikel-id 896Konferensbidrag (Refereegranskat)
    Abstract [en]

    Ren et al. [17] recently introduced a method for aggregating multiple decision trees into a strong predictor by interpreting a path taken by a sample down each tree as a binary vector and performing linear regression on top of these vectors stacked together. They provided experimental evidence that the method offers advantages over the usual approaches for combining decision trees (random forests and boosting). The method truly shines when the regression target is a large vector with correlated dimensions, such as a 2D face shape represented with the positions of several facial landmarks. However, we argue that their basic method is not applicable in many practical scenarios due to large memory requirements. This paper shows how this issue can be solved through the use of quantization and architectural changes of the predictor that maps decision tree-derived encodings to the desired output.

  • 253.
    Markus, Nenad
    et al.
    University of Zagreb.
    Pandzic, Igor
    University of Zagreb.
    Ahlberg, Jörgen
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Learning Local Descriptors by Optimizing the Keypoint-Correspondence Criterion2017Konferensbidrag (Refereegranskat)
    Abstract [en]

    Current best local descriptors are learned on a large dataset of matching and non-matching keypoint pairs. However, data of this kind is not always available since detailed keypoint correspondences can be hard to establish. On the other hand, we can often obtain labels for pairs of keypoint bags. For example, keypoint bags extracted from two images of the same object under different views form a matching pair, and keypoint bags extracted from images of different objects form a non-matching pair. On average, matching pairs should contain more corresponding keypoints than non-matching pairs. We describe an end-to-end differentiable architecture that enables the learning of local keypoint descriptors from such weakly-labeled data.

  • 254.
    Markus, Nenad
    et al.
    University of Zagreb, Croatia.
    Pandzic, Igor S.
    University of Zagreb, Croatia.
    Ahlberg, Jörgen
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Learning Local Descriptors by Optimizing the Keypoint-Correspondence Criterion2016Ingår i: 2016 23RD INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), IEEE COMPUTER SOC , 2016, s. 2380-2385Konferensbidrag (Refereegranskat)
    Abstract [en]

    Current best local descriptors are learned on a large dataset of matching and non-matching keypoint pairs. However, data of this kind is not always available since detailed keypoint correspondences can be hard to establish. On the other hand, we can often obtain labels for pairs of keypoint bags. For example, keypoint bags extracted from two images of the same object under different views form a matching pair, and keypoint bags extracted from images of different objects form a non-matching pair. On average, matching pairs should contain more corresponding keypoints than non-matching pairs. We describe an end-to-end differentiable architecture that enables the learning of local keypoint descriptors from such weakly-labeled data.

  • 255.
    Markus, Nenad
    et al.
    Univ Zagreb, Croatia.
    Pandzic, Igor S.
    Univ Zagreb, Croatia.
    Ahlberg, Jörgen
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Learning Local Descriptors by Optimizing the Keypoint-Correspondence Criterion: Applications to Face Matching, Learning From Unlabeled Videos and 3D-Shape Retrieval2019Ingår i: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042, Vol. 28, nr 1, s. 279-290Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Current best local descriptors are learned on a large data set of matching and non-matching keypoint pairs. However, data of this kind are not always available, since the detailed keypoint correspondences can be hard to establish. On the other hand, we can often obtain labels for pairs of keypoint bags. For example, keypoint bags extracted from two images of the same object under different views form a matching pair, and keypoint bags extracted from images of different objects form a non-matching pair. On average, matching pairs should contain more corresponding keypoints than non-matching pairs. We describe an end-to-end differentiable architecture that enables the learning of local keypoint descriptors from such weakly labeled data. In addition, we discuss how to improve the method by incorporating the procedure of mining hard negatives. We also show how our approach can be used to learn convolutional features from unlabeled video signals and 3D models.

  • 256.
    Markuš, Nenad
    et al.
    University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, Croatia.
    Fratarcangeli, Marco
    Chalmers University of Technology, Dept. of Applied Information Technology, Göteborg, Sweden.
    Pandžić, Igor
    University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, Croatia.
    Ahlberg, Jörgen
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Fast Rendering of Image Mosaics and ASCII Art2015Ingår i: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659, Vol. 34, nr 6, s. 251-261Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    An image mosaic is an assembly of a large number of small images, usually called tiles, taken from a specific dictionary/codebook. When viewed as a whole, the appearance of a single large image emerges, i.e. each tile approximates a small block of pixels. ASCII art is a related (and older) graphic design technique for producing images from printable characters. Although automatic procedures for both of these visualization schemes have been studied in the past, some are computationally heavy and cannot offer real-time and interactive performance. We propose an algorithm able to reproduce the quality of existing non-photorealistic rendering techniques, in particular ASCII art and image mosaics, obtaining large performance speed-ups. The basic idea is to partition the input image into a rectangular grid and use a decision tree to assign a tile from a pre-determined codebook to each cell. Our implementation can process video streams from webcams in real time and it is suitable for modestly equipped devices. We evaluate our technique by generating the renderings of a variety of images and videos, with good results. The source code of our engine is publicly available.

  • 257.
    Markuš, Nenad
    et al.
    University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, Croatia.
    Frljak, Miroslav
    University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, Croatia.
    Pandžić, Igor
    University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, Croatia.
    Ahlberg, Jörgen
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Forchheimer, Robert
    Linköpings universitet, Institutionen för systemteknik, Informationskodning. Linköpings universitet, Tekniska fakulteten.
    High-performance face tracking2012Konferensbidrag (Refereegranskat)
    Abstract [en]

    Face tracking is an extensively studied field. Nevertheless, it is still a challenge to make a robust and efficient face tracker, especially on mobile devices. This extended abstract briefly describes our implementation of a high-performance multi-platform face and facial feature tracking system. The main characteristics of our approach are that the tracker is fully automatic and works with the majority of faces without any manual initialization. It is robust, resistant to rapid changes in pose and facial expressions, does not suffer from drifting and is modestly computationally expensive. The tracker runs in real-time on mobile devices.

  • 258.
    Meneghetti, Giulia
    et al.
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för systemteknik, Datorseende.
    Danelljan, Martin
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för systemteknik, Datorseende.
    Felsberg, Michael
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för systemteknik, Datorseende.
    Nordberg, Klas
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för systemteknik, Datorseende.
    Image alignment for panorama stitching in sparsely structured environments2015Ingår i: Image Analysis. SCIA 2015. / [ed] Paulsen, Rasmus R., Pedersen, Kim S., Springer, 2015, s. 428-439Konferensbidrag (Refereegranskat)
    Abstract [en]

    Panorama stitching of sparsely structured scenes is an open research problem. In this setting, feature-based image alignment methods often fail due to shortage of distinct image features. Instead, direct image alignment methods, such as those based on phase correlation, can be applied. In this paper we investigate correlation-based image alignment techniques for panorama stitching of sparsely structured scenes. We propose a novel image alignment approach based on discriminative correlation filters (DCF), which has recently been successfully applied to visual tracking. Two versions of the proposed DCF-based approach are evaluated on two real and one synthetic panorama dataset of sparsely structured indoor environments. All three datasets consist of images taken on a tripod rotating 360 degrees around the vertical axis through the optical center. We show that the proposed DCF-based methods outperform phase correlation-based approaches on these datasets.

  • 259.
    Miandji, Ehsan
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Unger, Jonas
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    ON NONLOCAL IMAGE COMPLETION USING AN ENSEMBLE OF DICTIONARIES2016Ingår i: 2016 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), IEEE , 2016, s. 2519-2523Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper we consider the problem of nonlocal image completion from random measurements and using an ensemble of dictionaries. Utilizing recent advances in the field of compressed sensing, we derive conditions under which one can uniquely recover an incomplete image with overwhelming probability. The theoretical results are complemented by numerical simulations using various ensembles of analytical and training-based dictionaries.

  • 260.
    Mirabedini, Azadeh
    et al.
    ARC Centre of Excellence for Electromaterials Science, Intelligent Polymer Research Institute, AIIM Facility, University of Wollongong, Fairy Meadow, Australia.
    Aziz, Shazed
    ARC Centre of Excellence for Electromaterials Science, Intelligent Polymer Research Institute, AIIM Facility, University of Wollongong, Fairy Meadow, Australia.
    Spinks, Geoffrey M
    ARC Centre of Excellence for Electromaterials Science, Intelligent Polymer Research Institute, AIIM Facility, University of Wollongong, Fairy Meadow, Australia.
    Foroughi, Javad
    ARC Centre of Excellence for Electromaterials Science, Intelligent Polymer Research Institute, AIIM Facility, University of Wollongong, Fairy Meadow, Australia.
    Wet-Spun Biofiber for Torsional Artificial Muscles.2017Ingår i: Soft Robotics, ISSN 2169-5172, Vol. 4, nr 4, s. 421-430Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The demands for new types of artificial muscles continue to grow and novel approaches are being enabled by the advent of new materials and novel fabrication strategies. Self-powered actuators have attracted significant attention due to their ability to be driven by elements in the ambient environment such as moisture. In this study, we demonstrate the use of twisted and coiled wet-spun hygroscopic chitosan fibers to achieve a novel torsional artificial muscle. The coiled fibers exhibited significant torsional actuation where the free end of the coiled fiber rotated up to 1155 degrees per mm of coil length when hydrated. This value is 96%, 362%, and 2210% higher than twisted graphene fiber, carbon nanotube torsional actuators, and coiled nylon muscles, respectively. A model based on a single helix was used to evaluate the torsional actuation behavior of these coiled chitosan fibers.

  • 261.
    Molin, David
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Pedestrian Detection Using Convolutional Neural Networks2015Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Pedestrian detection is an important field with applications in active safety systems for cars as well as autonomous driving. Since autonomous driving and active safety are becoming technically feasible now the interest for these applications has dramatically increased.The aim of this thesis is to investigate convolutional neural networks (CNN) for pedestrian detection. The reason for this is that CNN have recently beensuccessfully applied to several different computer vision problems. The main applications of pedestrian detection are in real time systems. For this reason,this thesis investigates strategies for reducing the computational complexity offorward propagation for CNN.The approach used in this thesis for extracting pedestrians is to use a CNN tofind a probability map of where pedestrians are located. From this probabilitymap bounding boxes for pedestrians are generated. A method for handling scale invariance for the objects of interest has also been developed in this thesis. Experiments show that using this method givessignificantly better results for the problem of pedestrian detection.The accuracy which this thesis has managed to achieve is similar to the accuracy for some other works which use CNN.

  • 262.
    Molin, Joel
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Foreground Segmentation of Moving Objects2010Självständigt arbete på avancerad nivå (yrkesexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Foreground segmentation is a common first step in tracking and surveillance applications.  The purpose of foreground segmentation is to provide later stages of image processing with an indication of where interesting data can be found.  This thesis is an investigation of how foreground segmentation can be performed in two contexts: as a pre-step to trajectory tracking and as a pre-step in indoor surveillance applications.

    Three methods are selected and detailed: a single Gaussian method, a Gaussian mixture model method, and a codebook method.  Experiments are then performed on typical input video using the methods.  It is concluded that the Gaussian mixture model produces the output which yields the best trajectories when used as input to the trajectory tracker.  An extension is proposed to the Gaussian mixture model which reduces shadow, improving the performance of foreground segmentation in the surveillance context.

  • 263.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Tekniska högskolan.
    Borga, Magnus
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Tekniska högskolan.
    Smedby, Örjan
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Tekniska högskolan. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Soft classification of trabeculae in trabecular bone2011Ingår i: Biomedical Imaging: From Nano to Macro, 2011, IEEE , 2011, s. 1641-1644Konferensbidrag (Refereegranskat)
    Abstract [en]

    Classification of trabecular bone aims at discriminating different types of trabeculae. This paper proposes a method to perform a soft classification from binary 3D images. In a first step, the local structure tensor is used to estimate a membership degree of every voxel to three different classes, plate-, rod- and junction-like trabeculae. In a second step, the global structure tensor of plate-like trabeculae is compared with the local orientation of rod-like trabeculae in order to discriminate aligned from non-aligned rods. Results show that soft classification can be used for estimating independent parameters of trabecular bone for every different class, by using the classification as a weighting function.

  • 264.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Garcia, Miguel Angel
    Department of Informatics Engineering, Autonomous University of Madrid, Madrid, Spain.
    Puig, Domenec
    Intelligent Robotics and Computer Vision Group at the Department of Computer Science and Mathematics, Rovira i Virgili University, Tarragona, Spain.
    Julià, Carme
    Intelligent Robotics and Computer Vision Group at the Department of Computer Science and Mathematics, Rovira i Virgili University, Tarragona, Spain.
    Edge-Preserving Color Image Denoising Through Tensor Voting2011Ingår i: Computer Vision and Image Understanding, ISSN 1077-3142, E-ISSN 1090-235X, Vol. 115, nr 11, s. 1536-1551Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper presents a new method for edge-preserving color image denoising based on the tensor voting framework, a robust perceptual grouping technique used to extract salient information from noisy data. The tensor voting framework is adapted to encode color information through tensors in order to propagate them in a neighborhood by using a specific voting process. This voting process is specifically designed for edge-preserving color image denoising by taking into account perceptual color differences, region uniformity and edginess according to a set of intuitive perceptual criteria. Perceptual color differences are estimated by means of an optimized version of the CIEDE2000 formula, while uniformity and edginess are estimated by means of saliency maps obtained from the tensor voting process. Measurements of removed noise, edge preservation and undesirable introduced artifacts, additionally to visual inspection, show that the proposed method has a better performance than the state-of-the-art image denoising algorithms for images contaminated with CCD camera noise.

  • 265.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet.
    Pizarro, Luis
    Imperial College London, Department of Computing, UK.
    Burgeth, Bernhard
    Saarland University, Faculty of Mathematics and Computer Science, Germany.
    Weickert, Joachim
    Saarland University, Faculty of Mathematics and Computer Science, Germany .
    Garcia, Miguel Angel
    Autonomous University of Madrid, Department of Electronic and Communications Technology, Spain.
    Puig, Domenec
    Rovira i Virgili University, Department of Computer Science and Mathematics, Spain.
    Adaptation of Tensor Voting to Image Structure Estimation2012Ingår i: New Developments in the Visualization and Processing of Tensor Fields / [ed] David Laidlaw and Anna Vilanova, Springer Berlin/Heidelberg, 2012, s. 29-50Kapitel i bok, del av antologi (Övrigt vetenskapligt)
    Abstract [en]

    Bringing together key researchers in disciplines ranging from visualization and image processing to applications in structural mechanics, fluid dynamics, elastography, and numerical mathematics, the workshop that generated this edited volume was the third in the successful Dagstuhl series. Its aim, reflected in the quality and relevance of the papers presented, was to foster collaboration and fresh lines of inquiry in the analysis and visualization of tensor fields, which offer a concise model for numerous physical phenomena. Despite their utility, there remains a dearth of methods for studying all but the simplest ones, a shortage the workshops aim to address.Documenting the latest progress and open research questions in tensor field analysis, the chapters reflect the excitement and inspiration generated  by this latest Dagstuhl workshop, held in July 2009. The topics they address range from applications of the analysis of tensor fields to purer research into their mathematical and analytical properties. They show how cooperation and the sharing of ideas and data between those engaged in pure and applied research can open new vistas in the study of tensor fields

  • 266.
    Moulis, Armand
    Linköpings universitet, Institutionen för systemteknik, Datorseende.
    Automatic Detection and Classification of Permanent and Non-Permanent Skin Marks2017Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    När forensiker försöker identifiera förövaren till ett brott använder de individuella ansiktsmärken när de jämför den misstänkta med förövaren. Dessa ansiktsmärken identifieras och lokaliseras oftast manuellt idag. För att effektivisera denna process, är det önskvärt att detektera ansiktsmärken automatiskt. I rapporten beskrivs en framtagen metod som möjliggör automatiskt detektion och separation av permanenta och icke-permanenta ansiktsmärken. Metoden som är framtagen använder en snabb radial symmetri algoritm som en huvuddel i detektorn. När kandidater av ansiktsmärken har tagits, elimineras alla falska detektioner utifrån deras storlek, form och hårinnehåll. Utifrån studiens resultat visar sig detektorn ha en god känslighet men dålig precision. Eliminationsmetoderna av falska detektioner analyserades och olika attribut användes till klassificeraren. I rapporten kan det fastställas att färgskiftningar på ansiktsmärkena har en större inverkan än formen när det gäller att sortera dem i permanenta och icke-permanenta märken.

  • 267.
    Muhammad Anwer, Rao
    et al.
    Aalto University, Finland.
    Khan, Fahad
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    van de Weijer, Joost
    University of Autonoma Barcelona, Spain.
    Laaksonen, Jorma
    Aalto University, Finland.
    Combining Holistic and Part-based Deep Representations for Computational Painting Categorization2016Ingår i: ICMR16: PROCEEDINGS OF THE 2016 ACM INTERNATIONAL CONFERENCE ON MULTIMEDIA RETRIEVAL, ASSOC COMPUTING MACHINERY , 2016, s. 339-342Konferensbidrag (Refereegranskat)
    Abstract [en]

    Automatic analysis of visual art, such as paintings, is a challenging inter-disciplinary research problem. Conventional approaches only rely on global scene characteristics by encoding holistic information for computational painting categorization. We argue that such approaches are sub-optimal and that discriminative common visual structures provide complementary information for painting classification. We present an approach that encodes both the global scene layout and discriminative latent common structures for computational painting categorization. The region of interests are automatically extracted, without any manual part labeling, by training class-specific deformable part-based models. Both holistic and region-of-interests are then described using multi-scale dense convolutional features. These features are pooled separately using Fisher vector encoding and concatenated afterwards in a single image representation. Experiments are performed on a challenging dataset with 91 different painters and 13 diverse painting styles. Our approach outperforms the standard method, which only employs the global scene characteristics. Furthermore, our method achieves state-of-the-art results outperforming a recent multi-scale deep features based approach [11] by 6.4% and 3.8% respectively on artist and style classification.

  • 268.
    Muthumanickam, Prithiviraj
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Vrotsou, Katerina
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Cooper, Matthew
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Johansson, Jimmy
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Shape Grammar Extraction for Efficient Query-by-Sketch Pattern Matching in Long Time Series2016Konferensbidrag (Refereegranskat)
    Abstract [en]

    Long time-series, involving thousands or even millions of time steps, are common in many application domains but remain very difficult to explore interactively. Often the analytical task in such data is to identify specific patterns, but this is a very complex and computationally difficult problem and so focusing the search in order to only identify interesting patterns is a common solution. We propose an efficient method for exploring user-sketched patterns, incorporating the domain expert’s knowledge, in time series data through a shape grammar based approach. The shape grammar is extracted from the time series by considering the data as a combination of basic elementary shapes positioned across different am- plitudes. We represent these basic shapes using a ratio value, perform binning on ratio values and apply a symbolic approximation. Our proposed method for pattern matching is amplitude-, scale- and translation-invariant and, since the pattern search and pattern con- straint relaxation happen at the symbolic level, is very efficient permitting its use in a real-time/online system. We demonstrate the effectiveness of our method in a case study on stock market data although it is applicable to any numeric time series data.

  • 269.
    Nawaz, Tahir
    et al.
    Computational Vision Group, Department of Computer Science, University of Reading.
    Berg, Amanda
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten. Termisk Systemteknik AB, Linköping, Sweden.
    Ferryman, James
    Computational Vision Group, Department of Computer Science, University of Reading.
    Ahlberg, Jörgen
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten. Termisk Systemteknik AB, Linköping, Sweden.
    Felsberg, Michael
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Effective evaluation of privacy protection techniques in visible and thermal imagery2017Ingår i: Journal of Electronic Imaging (JEI), ISSN 1017-9909, E-ISSN 1560-229X, Vol. 26, nr 5, artikel-id 051408Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Privacy protection may be defined as replacing the original content in an image region with a new (less intrusive) content having modified target appearance information to make it less recognizable by applying a privacy protection technique. Indeed the development of privacy protection techniques needs also to be complemented with an established objective evaluation method to facilitate their assessment and comparison. Generally, existing evaluation methods rely on the use of subjective judgements or assume a specific target type in image data and use target detection and recognition accuracies to assess privacy protection. This work proposes a new annotation-free evaluation method that is neither subjective nor assumes a specific target type. It assesses two key aspects of privacy protection: protection and utility. Protection is quantified as an appearance similarity and utility is measured as a structural similarity between original and privacy-protected image regions. We performed an extensive experimentation using six challenging datasets (having 12 video sequences) including a new dataset (having six sequences) that contains visible and thermal imagery. The new dataset, called TST-Priv, is made available online below for community. We demonstrate effectiveness of the proposed method by evaluating six image-based privacy protection techniques, and also show comparisons of the proposed method over existing methods.

  • 270.
    Ng, Theam Foo
    et al.
    The University of New South Wales, ADFA, Canberra, Australia.
    Pham, Tuan D
    The University of New South Wales, ADFA, Canberra, Australia.
    Sun, Changming
    CSIRO Mathematics, Informatics and Statistics, Locked Bag 17, N. Ryde, Australia.
    Automated feature weighting in fuzzy declustering-based vector quantization2010Konferensbidrag (Refereegranskat)
    Abstract [en]

    Feature weighting plays an important role in improving the performance of clustering technique. We propose an automated feature weighting in fuzzy declustering-based vector quantization (FDVQ), namely AFDVQ algorithm, for enhancing effectiveness and efficiency in classification. The proposed AFDVQ imposes weights on the modified fuzzy c-means (FCM) so that it can automatically calculate feature weights based on their degrees of importance rather than treating them equally. Moreover, the extension of FDVQ and AFDVQ algorithms based on generalized improved fuzzy partitions (GIFP), known as GIFP-FDVQ and GIFP-AFDVQ respectively, are proposed. The experimental results on real data (original and noisy data) and modified data (biased and noisy-biased data) have demonstrated that the proposed algorithms outperformed standard algorithms in classifying clusters especially for biased data.

  • 271.
    Ng, Theam Foo
    et al.
    School of Engineering and Information Technology, The University of New South Wales, ADFA, Canberra, ACT 2600, Australia .
    Pham, Tuan D
    School of Engineering and Information Technology, The University of New South Wales, ADFA, Canberra, ACT 2600, Australia.
    Zhou, Xiaobo
    Center for Biotechnology and Informatics, The Methodist Hospital Research Institute, Weill Cornell Medical College, Houston, TX 77030, USA .
    Justification of Fuzzy Declustering Vector Quantization Modeling in Classification of Genotype-Image Phenotypes2010Konferensbidrag (Refereegranskat)
    Abstract [en]

    With the fast development of multi‐dimensional data compression and pattern classification techniques, vector quantization (VQ) has become a system that allows large reduction of data storage and computational effort. One of the most recent VQ techniques that handle the poor estimation of vector centroids due to biased data from undersampling is to use fuzzy declustering‐based vector quantization (FDVQ) technique. Therefore, in this paper, we are motivated to propose a justification of FDVQ based hidden Markov model (HMM) for investigating its effectiveness and efficiency in classification of genotype‐image phenotypes. The performance evaluation and comparison of the recognition accuracy between a proposed FDVQ based HMM (FDVQ‐HMM) and a well‐known LBG (Linde, Buzo, Gray) vector quantization based HMM (LBG‐HMM) will be carried out. The experimental results show that the performances of both FDVQ‐HMM and LBG‐HMM are almost similar. Finally, we have justified the competitiveness of FDVQ‐HMM in classification of cellular phenotype image database by using hypotheses t‐test. As a result, we have validated that the FDVQ algorithm is a robust and an efficient classification technique in the application of RNAi genome‐wide screening image data.

  • 272.
    Niemi, Mikael
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska högskolan.
    Machine Learning for Rapid Image Classification2013Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    In this thesis project techniques for training a rapid image classifier that can recognize an object of a predefined type has been studied. Classifiers have been trained with the AdaBoost algorithm, with and without the use of Viola-Jones cascades. The use of Weight trimming in the classifier training has been evaluated and resulted in a significant speed up of the training, as well as improving the performance of the trained classifier. Different preprocessings of the images have also been tested, but resulted for the most part in worse performance for the classifiers when used individually. Several rectangle shaped Haar-like features including novel versions have been evaluated and the magnitude versions proved to be best at separating the image classes.

  • 273.
    Nordberg, Klas
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Introduction to Representations and Estimation in Geometry2018Övrigt (Övrigt vetenskapligt)
    Abstract [en]

    This book contains material for an introductory course on homogeneous representations for geometry in 2 and 3 dimensions, camera projections, representations of 3D rotations, epipolar geometry, and estimation of various type of geometric objects. Based on these results, a set of applications are presented.  It also contains a toolbox of general results that are useful for the presented material.  The book is intended for undergraduate studies at advanced level in master programs, or in PhD-courses at introductory level.

  • 274.
    Nordberg, Klas
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Viksten, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Informationskodning. Linköpings universitet, Tekniska högskolan.
    A local geometry based descriptor for 3D data: Addendum on rank and segment extraction2010Rapport (Övrigt vetenskapligt)
    Abstract [en]

    This document is an addendum to the main text in A local geometry-based descriptor for 3D data applied to object pose estimation by Fredrik Viksten and Klas Nordberg. This addendum gives proofs for propositions stated in the main document. This addendum also details how to extract information from the fourth order tensor refered to as S22 in the main document.

  • 275.
    Nordgaard, Anders
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Statistik. Linköpings universitet, Filosofiska fakulteten.
    Höglund, Tobias
    Statens Kriminaltekniska Laboratorium.
    Assessment of Approximate Likelihood Ratios from Continuous Distributions: A Case Study of Digital Camera Identification2011Ingår i: Journal of Forensic Sciences, ISSN 0022-1198, E-ISSN 1556-4029, Vol. 56, nr 2, s. 390-402Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A reported likelihood ratio for the value of evidence is very often a point estimate based on various types of reference data. When presented in court, such frequentist likelihood ratio gets a higher scientific value if it is accompanied by an error bound. This becomes particularly important when the magnitude of the likelihood ratio is modest and thus is giving less support for the forwarded proposition. Here, we investigate methods for error bound estimation for the specific case of digital camera identification. The underlying probability distributions are continuous and previously proposed models for those are used, but the derived methodology is otherwise general. Both asymptotic and resampling distributions are applied in combination with different types of point estimators. The results show that resampling is preferable for assessment based on asymptotic distributions. Further, assessment of parametric estimators is superior to evaluation of kernel estimators when background data are limited.

  • 276.
    Nordgaard, Anders
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Statistik. Linköpings universitet, Filosofiska fakulteten.
    Höglund, Tobias
    Swedish National Laboratory of Forensic Sciences.
    The use of likelihood ratios in digital camera identification2008Ingår i: The Seventh International Conference on Forensic Inference and Statistics, Lausanne, CH, 2008Konferensbidrag (Övrigt vetenskapligt)
  • 277.
    Norström, Christer
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Underwater 3-D imaging with laser triangulation2006Självständigt arbete på grundnivå (yrkesexamen), 20 poäng / 30 hpStudentuppsats
    Abstract [en]

    The objective of this master thesis was to study the performance of an active triangulation system for 3-D imaging in underwater applications. Structured light from a 20 mW laser and a conventional video camera was used to collect data for generation of 3-D images. Different techniques to locate the laser line and transform it into spatial coordinates were developed and evaluated. A field- and a laboratory trial were performed.

    From the trials we can conclude that the distance resolution is much higher than the lateral- and longitudinal resolution. The lateral resolution can be improved either by using a high frame rate camera or simply by using a low scanning speed. It is possible to obtain a range resolution of less than a millimeter. The maximum range of vision was 5 meters under water measured on a white target and 3 meters for a black target in clear sea water. These results are however dependent on environmental and system parameters such as laser power, laser beam divergence and water turbidity. A higher laser power would for example increase the maximum range.

  • 278.
    Norén, Karl
    Linköpings universitet, Institutionen för datavetenskap, Programvara och system.
    Obstacle Avoidance for an Autonomous Robot Car using Deep Learning2019Självständigt arbete på grundnivå (kandidatexamen), 10,5 poäng / 16 hpStudentuppsats (Examensarbete)
    Abstract [en]

    The focus of this study was deep learning. A small, autonomous robot car was used for obstacle avoidance experiments. The robot car used a camera for taking images of its surroundings. A convolutional neural network used the images for obstacle detection. The available dataset of 31 022 images was trained with the Xception model. We compared two different implementations for making the robot car avoid obstacles. Mapping image classes to steering commands was used as a reference implementation. The main implementation of this study was to separate obstacle detection and steering logic in different modules. The former reached an obstacle avoidance ratio of 80 %, the latter reached 88 %. Different hyperparameters were looked at during training. We found that frozen layers and number of epochs were important to optimize. Weights were loaded from ImageNet before training. Frozen layers decided how many layers that were trainable after that. Training all layers (no frozen layers) was proven to work best. Number of epochs decided how many epochs a model trained. We found that it was important to train between 10-25 epochs. The best model used no frozen layers and trained for 21 epochs. It reached a test accuracy of 85.2 %.

  • 279.
    Nyberg, Adam
    Linköpings universitet, Institutionen för systemteknik, Datorseende.
    Transforming Thermal Images to Visible Spectrum Images Using Deep Learning2018Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Thermal spectrum cameras are gaining interest in many applications due to their long wavelength which allows them to operate under low light and harsh weather conditions. One disadvantage of thermal cameras is their limited visual interpretability for humans, which limits the scope of their applications. In this thesis, we try to address this problem by investigating the possibility of transforming thermal infrared (TIR) images to perceptually realistic visible spectrum (VIS) images by using Convolutional Neural Networks (CNNs). Existing state-of-the-art colorization CNNs fail to provide the desired output as they were trained to map grayscale VIS images to color VIS images. Instead, we utilize an auto-encoder architecture to perform cross-spectral transformation between TIR and VIS images. This architecture was shown to quantitatively perform very well on the problem while producing perceptually realistic images. We show that the quantitative differences are insignificant when training this architecture using different color spaces, while there exist clear qualitative differences depending on the choice of color space. Finally, we found that a CNN trained from daytime examples generalizes well on tests from night time. 

  • 280.
    Nyberg, Adam
    Linköpings universitet, Institutionen för systemteknik. Linköpings universitet, Tekniska fakulteten.
    Transforming Thermal Images to Visible Spectrum Images using Deep Learning2018Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Thermal spectrum cameras are gaining interest in many applications due to their long wavelength which allows them to operate under low light and harsh weather conditions. One disadvantage of thermal cameras is their limited visual interpretability for humans, which limits the scope of their applications. In this thesis, we try to address this problem by investigating the possibility of transforming thermal infrared (TIR) images to perceptually realistic visible spectrum (VIS) images by using Convolutional Neural Networks (CNNs). Existing state-of-the-art colorization CNNs fail to provide the desired output as they were trained to map grayscale VIS images to color VIS images. Instead, we utilize an auto-encoder architecture to perform cross-spectral transformation between TIR and VIS images. This architecture was shown to quantitatively perform very well on the problem while producing perceptually realistic images. We show that the quantitative differences are insignificant when training this architecture using different color spaces, while there exist clear qualitative differences depending on the choice of color space. Finally, we found that a CNN trained from day time examples generalizes well on tests from night time.

  • 281.
    Nyqvist, Hanna E.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    On Pose Estimation in Room-Scaled Environments2016Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Pose (position and orientation) tracking in room-scaled environments is an enabling technique for many applications. Today, virtual reality (vr) and augmented reality (ar) are two examples of such applications, receiving high interest both from the public and the research community. Accurate pose tracking of the vr or ar equipment, often a camera or a headset, or of different body parts is crucial to trick the human brain and make the virtual experience realistic. Pose tracking in room-scaled environments is also needed for reference tracking and metrology. This thesis focuses on an application to metrology. In this application, photometric models of a photo studio are needed to perform realistic scene reconstruction and image synthesis. Pose tracking of a dedicated sensor enables creation of these photometric models. The demands on the tracking system used in this application is high. It must be able to provide sub-centimeter and sub-degree accuracy and at same time be easy to move and install in new photo studios.

    The focus of this thesis is to investigate and develop methods for a pose tracking system that satisfies the requirements of the intended metrology application. The Bayesian filtering framework is suggested because of its firm theoretical foundation in informatics and because it enables straightforward fusion of measurements from several sensors. Sensor fusion is in this thesis seen as a way to exploit complementary characteristics of different sensors to increase tracking accuracy and robustness. Four different types of measurements are considered; inertialmeasurements, images from a camera, range (time-of-flight) measurements from ultra wide band (uwb) radio signals, and range and velocity measurements from echoes of transmitted acoustic signals.

    A simulation study and a study of the Cramér-Rao lower filtering bound (crlb) show that an inertial-camera system has the potential to reach the required tracking accuracy. It is however assumed that known fiducial markers, that can be detected and recognized in images, are deployed in the environment. The study shows that many markers are required. This makes the solution more of a stationary solution and the mobility requirement is not fulfilled. A simultaneous localization and mapping (slam) solution, where naturally occurring features are used instead of known markers, are suggested solve this problem. Evaluation using real data shows that the provided inertial-camera slam filter suffers from drift but that support from uwb range measurements eliminates this drift. The slam solution is then only dependent on knowing the position of very few stationary uwb transmitters compared to a large number of known fiducial markers. As a last step, to increase the accuracy of the slam filter, it is investigated if and how range measurements can be complemented with velocity measurement obtained as a result of the Doppler effect. Especially, focus is put on analyzing the correlation between the range and velocity measurements and the implications this correlation has for filtering. The investigation is done in a theoretical study of reflected known signals (compare with radar and sonar) where the crlb is used as an analyzing tool. The theory is validated on real data from acoustic echoes in an indoor environment.

    Delarbeten
    1. A High-Performance Tracking System based on Camera and IMU
    Öppna denna publikation i ny flik eller fönster >>A High-Performance Tracking System based on Camera and IMU
    2013 (Engelska)Ingår i: 16th International Conference on Information Fusion (FUSION), 2013, IEEE , 2013, s. 2065-2072Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    We consider an indoor tracking system consisting of an inertial measurement unit (IMU) and a camera that detects markers in the environment. There are many camera based tracking systems described in literature and available commercially, and a few of them also has support from IMU. These are based on the best-effort principle, where the performance varies depending on the situation. In contrast to this, we start with a specification of the system performance, and the design isbased on an information theoretic approach, where specific user scenarios are defined. Precise models for the camera and IMU are derived for a fusion filter, and the theoretical Cramér-Rao lower bound and the Kalman filter performance are evaluated. In this study, we focus on examining the camera quality versus the marker density needed to get at least a one mm and one degree accuracy in tracking performance.

    Ort, förlag, år, upplaga, sidor
    IEEE, 2013
    Nyckelord
    Tracking, IMU, Vision, Indoor, Landmarks, Cameras, Lenses, Earth, Accuracy, Optical sensors, Noise, Optical imaging
    Nationell ämneskategori
    Reglerteknik
    Identifikatorer
    urn:nbn:se:liu:diva-96751 (URN)000341370000274 ()9786058631113 (ISBN)9781479902842 (ISBN)9786058631113 (ISBN)
    Konferens
    2013 16th International Conference on Information Fusion, Istanbul, Turkey, July 9-12, 2013
    Projekt
    VPS
    Forskningsfinansiär
    Stiftelsen för strategisk forskning (SSF)
    Tillgänglig från: 2013-08-26 Skapad: 2013-08-26 Senast uppdaterad: 2016-11-22Bibliografiskt granskad
    2. Pose Estimation Using Monocular Vision and Inertial Sensors Aided with Ultra Wide Band
    Öppna denna publikation i ny flik eller fönster >>Pose Estimation Using Monocular Vision and Inertial Sensors Aided with Ultra Wide Band
    2015 (Engelska)Ingår i: International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2015, IEEE , 2015Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    This paper presents a method for global pose estimation using inertial sensors, monocular vision, and ultra wide band (UWB) sensors. It is demonstrated that the complementary characteristics of these sensors can be exploited to provide improved global pose estimates, without requiring the introduction of any visible infrastructure, such as fiducial markers. Instead, natural landmarks are jointly estimated with the pose of the platform using a simultaneous localization and mapping framework, supported by a small number of easy-to-hide UWB beacons with known positions. The method is evaluated with data from a controlled indoor experiment with high precision ground truth. The results show the benefit of the suggested sensor combination and suggest directions for further work.

    Ort, förlag, år, upplaga, sidor
    IEEE, 2015
    Nyckelord
    inertial sensor (IMU), ultra wide band (UWB), monocular camera, simultaneous localization and mapping (SLAM)
    Nationell ämneskategori
    Signalbehandling Reglerteknik
    Identifikatorer
    urn:nbn:se:liu:diva-122140 (URN)10.1109/IPIN.2015.7346940 (DOI)000379160900049 ()9781467384025 (ISBN)9781467384018 (ISBN)
    Konferens
    Sixth International Conference on Indoor Positioning and Indoor Navigation, Banff, October 13-16, 2015
    Projekt
    Virtual Photo Studio (VPS)
    Forskningsfinansiär
    Stiftelsen för strategisk forskning (SSF), IIS11-0081VetenskapsrådetSecurity Link
    Tillgänglig från: 2015-10-20 Skapad: 2015-10-20 Senast uppdaterad: 2016-11-22Bibliografiskt granskad
    3. On Joint Range and Velocity Estimation in Detection and Ranging Sensors
    Öppna denna publikation i ny flik eller fönster >>On Joint Range and Velocity Estimation in Detection and Ranging Sensors
    2016 (Engelska)Ingår i: Proceedings of 19th International Conference on Information Fusion (FUSION), Institute of Electrical and Electronics Engineers (IEEE), 2016, s. 1674-1681Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    Radar and sonar provide information of both range and radial velocity to unknown objects. This is accomplished by emitting a signal waveform and computing the round trip time and Doppler shift. Estimation of the round trip time and Doppler shift is usually done separately without considering the couplings between these two object related quantities. The purpose of this contribution is to first model the amplitude, time shift and time scale of the returned signal in terms of the object related states range and velocity, and analyse the Cramér-Rao lower bound (CRLB) for the joint range and velocity estimation problem. One of the conclusions is that there is negative correlation between range and velocity. The maximum likelihood (ML) cost function also confirms this strong negative correlation. For target tracking applications, the use of the correct covariance matrix for the measurement vector gives a significant gain in information, compared to using the variance of range and velocity assuming independence. In other words, the knowledge of the correlation tells the tracking filter that a too large range measurement comes most likely with a too small velocity measurement, and vice versa. Experiments with sound pulses reflected in a wall indoors confirm the main conclusion of negative correlation.

    Ort, förlag, år, upplaga, sidor
    Institute of Electrical and Electronics Engineers (IEEE), 2016
    Nyckelord
    Cramér-Rao lower bound (CRLB), time scale, Doppler shift, time shift, time delay, tracking
    Nationell ämneskategori
    Reglerteknik Signalbehandling
    Identifikatorer
    urn:nbn:se:liu:diva-130476 (URN)000391273400222 ()9780996452748 (ISBN)9781509020126 (ISBN)
    Konferens
    19th International Conference on Information Fusion, Heidelberg, Germany, July 5-8, 2016
    Projekt
    Virtual Photo Studio (VPS)Scalable Kalman Filters
    Forskningsfinansiär
    Stiftelsen för strategisk forskning (SSF), IIS11-0081Vetenskapsrådet
    Tillgänglig från: 2016-08-09 Skapad: 2016-08-09 Senast uppdaterad: 2017-02-03Bibliografiskt granskad
  • 282.
    Nyström, Daniel
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Digitala Medier. Linköpings universitet, Tekniska högskolan.
    Colorimetric and Multispectral Image Acquisition2006Licentiatavhandling, monografi (Övrigt vetenskapligt)
    Abstract [en]

    The trichromatic principle of representing color has for a long time been dominating in color imaging. The reason is the trichromatic nature of human color vision, but as the characteristics of typical color imaging devices are different from those of human eyes, there is a need to go beyond the trichromatic approach. The interest for multi-channel imaging, i.e. increasing the number of color channels, has made it an active research topic with a substantial potential of application.

    To achieve consistent color imaging, one needs to map the imaging-device data to the device-independent colorimetric representations CIEXYZ or CIELAB, the key concept of color management. As the color coordinates depend not only on the reflective spectrum of the object but also on the spectral properties of the illuminant, the colorimetric representation suffers from metamerism, i.e. objects of the same color under a specific illumination may appear different when they are illuminated by other light sources. Furthermore, when the sensitivities of the imaging device differ from the CIE color matching functions, two spectra that appear different for human observers may result in identical device response. On contrary, in multispectral imaging, color is represented by the object’s physical characteristics namely the spectrum which is illuminant independent. With multispectral imaging, different spectra are readily distinguishable, no matter they are metameric or not. The spectrum can then be transformed to any color space and be rendered under any illumination.

    The focus of the thesis is high quality image-acquisition in colorimetric and multispectral formats. The image acquisition system used is an experimental system with great flexibility in illumination and image acquisition setup. Besides the conventional trichromatic RGB filters, the system also provides the possibility of acquiring multi-channel images, using 7 narrowband filters. A thorough calibration and characterization of all the components involved in the image acquisition system is carried out. The spectral sensitivity of the CCD camera, which can not be derived by direct measurements, is estimated using least squares regression, optimizing the camera response to measured spectral reflectance of carefully selected color samples.

    To derive mappings to colorimetric and multispectral representations, two conceptually different approaches are used. In the model-based approach, the physical model describing the image acquisition process is inverted, to reconstruct spectral reflectance from the recorded device response. In the empirical approach, the characteristics of the individual components are ignored, and the functions are derived by relating the device response for a set of test colors to the corresponding colorimetric and spectral measurements, using linear and polynomial least squares regression.

    The results indicate that for trichromatic imaging, accurate colorimetric mappings can be derived by the empirical approach, using polynomial regression to CIEXYZ and CIELAB. Because of the media-dependency, the characterization functions should be derived for each combination of media and colorants. However, accurate spectral data reconstruction requires for multi-channel imaging, using the model-based approach. Moreover, the model-based approach is general, since it is based on the spectral characteristics of the image acquisition system, rather than the characteristics of a set of color samples.

  • 283.
    Nyström, Daniel
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Digitala Medier. Linköpings universitet, Tekniska högskolan.
    High Resolution Analysis of Halftone Prints: A Colorimetric and Multispectral Study2009Doktorsavhandling, monografi (Övrigt vetenskapligt)
    Abstract [en]

    To reproduce color images in print, the continuous tone image is first transformed into a binary halftone image, producing various colors by discrete dots with varying area coverage. In halftone prints on paper, physical and optical dot gains generally occur, making the print look darker than expected, and making the modeling of halftone color reproduction a challenge. Most available models are based on macroscopic color measurements, averaging the reflectance over an area that is large in relation to the halftone dots. The aim of this study is to go beyond the macroscopic approach, and study halftone color reproduction on a micro-scale level, using high resolution images of halftone prints. An experimental imaging system, combining the accuracy of color measurement instruments with a high spatial resolution, opens up new possibilities to study and analyze halftone color prints.

    The experimental image acquisition offers a great flexibility in the image acquisition setup. Besides trichromatic RGB filters, the system is also equipped with a set of 7 narrowband filters, for multi-channel images. A thorough calibration and characterization of all the components in the imaging system is described. The spectral sensitivity of the CCD camera, which can not be derived by direct measurements, is estimated using least squares regression. To reconstruct spectral reflectance and colorimetric values from the device response, two conceptually different approaches are used. In the model-based characterization, the physical model describing the image acquisition process is inverted, to reconstruct spectral reflectance from the recorded device response. In the empirical characterization, the characteristics of the individual components are ignored, and the functions are derived by relating the device response for a set of test colors to the corresponding colorimetric and spectral measurements, using linear and polynomial least squares regression techniques.

    Micro-scale images, referring to images whose resolution is high in relation to the resolution of the halftone, allow for measurements of the individual halftone dots, as well as the paper between them. To capture the characteristics of large populations of halftone dots, reflectance histograms are computed as well as 3D histograms in CIEXYZ color space. The micro-scale measurements reveal that the reflectance for the halftone dots, as well as the paper between the dots, is not constant, but varies with the dot area coverage. By incorporating the varying micro-reflectance in an expanded Murray-Davies model, the nonlinearity caused by optical dot gain can be accounted for without applying the nonphysical exponentiation of the reflectance values, as in the commonly used Yule-Nielsen model.

    Due to their different intrinsic nature, physical and optical dot gains need to be treated separately when modeling the outcome of halftone prints. However, in measurements of reflection colors, physical and optical dot gains always co-exist, making the separation a difficult task. Different methods to separate the physical and optical dot gain are evaluated, using spectral reflectance measurements, transmission scans and micro-scale images. Further, the relation between the physical dot gain and the halftone dot size is investigated, demonstrated with FM halftones of various print resolutions. The physical dot gain exhibits a clear correlation with the dot size and the dot gain increase is proportional to the increase in print resolution. The experimental observations are followed by discussions and a theoretical explanation.

  • 284.
    Ochs, Matthias
    et al.
    Goethe Univ, Germany.
    Bradler, Henry
    Goethe Univ, Germany.
    Mester, Rudolf
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten. Goethe Univ, Germany.
    Learning Rank Reduced Interpolation with Principal Component Analysis2017Ingår i: 2017 28TH IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV 2017), IEEE , 2017, s. 1126-1133Konferensbidrag (Refereegranskat)
    Abstract [en]

    Most iterative optimization algorithms for motion, depth estimation or scene reconstruction, both sparse and dense, rely on a coarse and reliable dense initialization to bootstrap their optimization procedure. This makes techniques important that allow to obtain a dense but still approximative representation of a desired 2D structure (e.g., depth maps, optical flow, disparity maps) from a very sparse measurement of this structure. The method presented here exploits the complete information given by the principal component analysis (PCA), the principal basis and its prior distribution. The method is able to determine a dense reconstruction even if only a very sparse measurement is available. When facing such situations, typically the number of principal components is further reduced which results in a loss of expressiveness of the basis. We overcome this problem and inject prior knowledge in a maximum a posteriori (MAP) approach. We test our approach on the KITTI and the Virtual KITTI dataset and focus on the interpolation of depth maps for driving scenes. The evaluation of the results shows good agreement to the ground truth and is clearly superior to the results of an interpolation by the nearest neighbor method which disregards statistical information.

  • 285.
    Ogniewski, Jens
    et al.
    Linköpings universitet, Institutionen för systemteknik, Informationskodning. Linköpings universitet, Tekniska fakulteten.
    Forssén, Per-Erik
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Pushing the Limits for View Prediction in Video Coding2017Ingår i: 12th International Conference on Computer Vision Theory and Applications (VISAPP’17), Scitepress Digital Library , 2017Konferensbidrag (Refereegranskat)
    Abstract [en]

    The ability to direct visual attention is a fundamental skill for seeing robots. Attention comes in two flavours: the gaze direction (overt attention) and attention to a specific part of the current field of view (covert attention), of which the latter is the focus of the present study. Specifically, we study the effects of attentional masking within pre-trained deep neural networks for the purpose of handling ambiguous scenes containing multiple objects. We investigate several variants of attentional masking on partially pre-trained deep neural networks and evaluate the effects on classification performance and sensitivity to attention mask errors in multi-object scenes. We find that a combined scheme consisting of multi-level masking and blending provides the best trade-off between classification accuracy and insensitivity to masking errors. This proposed approach is denoted multilayer continuous-valued convolutional feature masking (MC-CFM). For reasonably accurate masks it can suppress the influence of distracting objects and reach comparable classification performance to unmasked recognition in cases without distractors.

  • 286.
    Ogniewski, Jens
    et al.
    Linköpings universitet, Institutionen för systemteknik, Informationskodning. Linköpings universitet, Tekniska fakulteten.
    Forssén, Per-Erik
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Pushing the Limits for View Prediction in Video Coding2017Ingår i: PROCEEDINGS OF THE 12TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISIGRAPP 2017), VOL 4, SCITEPRESS , 2017, s. 68-76Konferensbidrag (Refereegranskat)
    Abstract [en]

    More and more devices have depth sensors, making RGB+D video (colour+depth video) increasingly common. RGB+D video allows the use of depth image based rendering (DIBR) to render a given scene from different viewpoints, thus making it a useful asset in view prediction for 3D and free-viewpoint video coding. In this paper we evaluate a multitude of algorithms for scattered data interpolation, in order to optimize the performance of DIBR for video coding. This also includes novel contributions like a Kriging refinement step, an edge suppression step to suppress artifacts, and a scale-adaptive kernel. Our evaluation uses the depth extension of the Sintel datasets. Using ground-truth sequences is crucial for such an optimization, as it ensures that all errors and artifacts are caused by the prediction itself rather than noisy or erroneous data. We also present a comparison with the commonly used mesh-based projection.

  • 287.
    Ogniewski, Jens
    et al.
    Linköpings universitet, Institutionen för systemteknik, Informationskodning. Linköpings universitet, Tekniska fakulteten.
    Forssén, Per-Erik
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    What is the best depth-map compression for Depth Image Based Rendering?2017Ingår i: Computer Analysis of Images and Patterns: 17th International Conference, CAIP 2017, Ystad, Sweden, August 22-24, 2017, Proceedings, Part II / [ed] Michael Felsberg, Anders Heyden and Norbert Krüger, Springer, 2017, Vol. 10425, s. 403-415Konferensbidrag (Refereegranskat)
    Abstract [en]

    Many of the latest smart phones and tablets come with integrated depth sensors, that make depth-maps freely available, thus enabling new forms of applications like rendering from different view points. However, efficient compression exploiting the characteristics of depth-maps as well as the requirements of these new applications is still an open issue. In this paper, we evaluate different depth-map compression algorithms, with a focus on tree-based methods and view projection as application.

    The contributions of this paper are the following: 1. extensions of existing geometric compression trees, 2. a comparison of a number of different trees, 3. a comparison of them to a state-of-the-art video coder, 4. an evaluation using ground-truth data that considers both depth-maps and predicted frames with arbitrary camera translation and rotation.

    Despite our best efforts, and contrary to earlier results, current video depth-map compression outperforms tree-based methods in most cases. The reason for this is likely that previous evaluations focused on low-quality, low-resolution depth maps, while high-resolution depth (as needed in the DIBR setting) has been ignored up until now. We also demonstrate that PSNR on depth-maps is not always a good measure of their utility.

  • 288.
    Olausson, Erik
    Linköpings universitet, Institutionen för teknik och naturvetenskap.
    Face Recognition for Mobile Phone Applications2008Självständigt arbete på avancerad nivå (magisterexamen), 20 poäng / 30 hpStudentuppsats
    Abstract [sv]

    Att applicera ansiktsigenkänning direkt på en mobiltelefon är en utmanande uppgift, inte minst med tanke på den begränsade minnes- och processorkapaciteten samt den stora variationen med avseende på ansiktsuttryck, hållning och ljusförhållande i inmatade bilder.

    Det är fortfarande långt kvar till ett färdigutvecklat, robust och helautomatiskt ansiktsigenkänningssystem för den här miljön. Men resultaten i det här arbetet visar att genom att plocka ut feature-värden från lokala regioner samt applicera en välgjord warpstrategi för att minska problemen med variationer i position och rotation av huvudet, är det möjligt att uppnå rimliga och användbara igenkänningsnivåer. Speciellt för ett halvautomatiskt system där användaren har sista ordet om vem personen på bilden faktiskt är.

    Med ett galleri bestående av 85 personer och endast en referensbild per person nådde systemet en igenkänningsgrad på 60% på en svårklassificerad serie testbilder. Totalt 73% av gångerna var den rätta individen inom de fyra främsta gissningarna.

    Att lägga till extra referensbilder till galleriet höjer igenkänningsgraden rejält, till nästan 75% för helt korrekta gissningar och till 83,5% för topp fyra. Detta visar att en strategi där inmatade bilder läggs till som referensbilder i galleriet efterhand som de identifieras skulle löna sig ordentligt och göra systemet bättre efter hand likt en inlärningsprocess.

    Detta exjobb belönades med pris för "Bästa industrirelevanta bidrag" vid Svenska sällskapet för automatiserad bildanalys årliga konferens i Lund, 13-14 mars 2008.

  • 289.
    Olgemar, Markus
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Camera Based Navigation: Matching between Sensor reference and Video image2008Självständigt arbete på avancerad nivå (yrkesexamen), 20 poäng / 30 hpStudentuppsats
    Abstract [en]

    an Internal Navigational System and a Global Navigational Satellite System (GNSS). In navigational warfare the GNSS can be jammed, therefore are a third navigational system is needed. The system that has been tried in this thesis is camera based navigation. Through a video camera and a sensor reference the position is determined. This thesis will process the matching between the sensor reference and the video image.

    Two methods have been implemented: normalized cross correlation and position determination through a homography. Normalized cross correlation creates a correlation matrix. The other method uses point correspondences between the images to determine a homography between the images. And through the homography obtain a position. The more point correspondences the better the position determination will be.

    The results have been quite good. The methods have got the right position when the Euler angles of the UAV have been known. Normalized cross correlation has been the best method of the tested methods.

  • 290.
    Olofsson, Anders
    Linköpings universitet, Institutionen för systemteknik, Informationskodning.
    Modern Stereo Correspondence Algorithms: Investigation and Evaluation2010Självständigt arbete på avancerad nivå (yrkesexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Many different approaches have been taken towards solving the stereo correspondence problem and great progress has been made within the field during the last decade. This is mainly thanks to newly evolved global optimization techniques and better ways to compute pixel dissimilarity between views. The most successful algorithms are based on approaches that explicitly model smoothness assumptions made about the physical world, with image segmentation and plane fitting being two frequently used techniques.

    Within the project, a survey of state of the art stereo algorithms was conducted and the theory behind them is explained. Techniques found interesting were implemented for experimental trials and an algorithm aiming to achieve state of the art performance was implemented and evaluated. For several cases, state of the art performance was reached.

    To keep down the computational complexity, an algorithm relying on local winner-take-all optimization, image segmentation and plane fitting was compared against minimizing a global energy function formulated on pixel level. Experiments show that the local approach in several cases can match the global approach, but that problems sometimes arise – especially when large areas that lack texture are present. Such problematic areas are better handled by the explicit modeling of smoothness in global energy minimization.

    Lastly, disparity estimation for image sequences was explored and some ideas on how to use temporal information were implemented and tried. The ideas mainly relied on motion detection to determine parts that are static in a sequence of frames. Stereo correspondence for sequences is a rather new research field, and there is still a lot of work to be made.

  • 291.
    Olsson, Martin
    Linköpings universitet, Institutionen för teknik och naturvetenskap.
    Obstacle detection using stereo vision for unmanned ground vehicles2009Självständigt arbete på avancerad nivå (yrkesexamen), 20 poäng / 30 hpStudentuppsats
    Abstract [en]

    In recent years, the market for automatized surveillance and use of unmanned ground vehicles (UGVs) has increased considerably. In order for unmanned vehicles to operate autonomously, high level algorithms of artificial intelligence need to be developed and accompanied by some way to make the robots perceive and interpret the environment. The purpose of this work is to investigate methods for real-time obstacle detection using stereo vision and implement these on an existing UGV platform. To reach real-time processing speeds, the algorithms presented in this work are designed for parallel processing architectures and implemented using programmable graphics hardware. The reader will be introduced to the basics of stereo vision and given an overview of the most common real-time stereo algorithms in literature along with possible applications. A novel wide-baseline real-time depth estimation algorithm is presented. The depth estimation is used together with a simple obstacle detection algorithm, producing an occupancy map of the environment allowing for evasion of obstacles and path planning. In addition, a complete system design for autonomous navigation in multi-UGV systems is proposed.

  • 292. Olwal, Alex
    et al.
    Henrysson, Anders
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Visuell informationsteknologi och applikationer. Linköpings universitet, Tekniska högskolan.
    LUMAR: A Hybrid Spatial Display System for 2D and 3D Handheld Augmented Reality2007Ingår i: 17th International Conference on Artificial Reality and Telexistence (ICAT 2007), Esbjerg, Denmark, 2007, Los Alamitos, CA, USA: IEEE Computer Society Press , 2007, s. 63-70Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    LUMAR is a hybrid system for spatial displays, allowing cell phones to be tracked in 2D and 3D through combined egocentric and exocentric techniques based on the Light-Sense and UMAR frameworks. LUMAR differs from most other spatial display systems based on mobile phones with its three-layered information space. The hybrid spatial display system consists of printed matter that is augmented with context-sensitive, dynamic 2D media when the device is on the surface, and with overlaid 3D visualizations when it is held in mid-air.

  • 293.
    Othberg, Fredrik
    Linköpings universitet, Institutionen för teknik och naturvetenskap.
    Standardized Volume Rendering Protocols for Magnetic Resonance Imaging using Maximum-Likelihood Modeling2006Självständigt arbete på avancerad nivå (magisterexamen), 20 poäng / 30 hpStudentuppsats
    Abstract [en]

    Volume rendering (VRT) has been used with great success in studies of patients using computed tomography (CT), much because of the possibility of standardizing the rendering protocols. When using magnetic resonance imaging (MRI), this procedure is considerably more difficult, since the signal from a given tissue can vary dramatically, even for the same patient. This thesis work focuses on how to improve the presentation of MRI data by using VRT protocols including standardized transfer functions. The study is limited to exclusively examining data from patients with suspected renal artery stenosis. A total number of 11 patients are examined.

    A statistical approach is used to standardize the volume rendering protocols. The histogram of the image volume is modeled as the sum of two gamma distributions, corresponding to vessel and background voxels. Parameters describing the gamma distributions are estimated with a Maximum-likelihood technique, so that expectation (E1 and E2) and standard deviation of the two voxel distributions can be calculated from the histogram. These values are used to generate the transfer function.

    Different combinations of the values from the expectation and standard deviation were studied in a material of 11 MR angiography datasets, and the visual result was graded by a radiologist. By comparing the grades, it turned out that using only the expectation of the background distribution (E1) and vessel distribution (E2) gave the best result. The opacity is then defined with a value of 0 up to a signal threshold of E1, then increasing linearly up to 50 % at a second threshold E2, and after that a constant opacity of 50 %. The brightness curve follows the opacity curve to E2, after which it continues to increase linearly up to 100%.

    A graphical user interface was created to facilitate the user-control of the volumes and transfer functions. The result from the statistical calculations is displayed in the interface and is used to view and manipulate the transfer function directly in the volume histogram.

    A transfer function generated with the Maximum-likelihood VRT method (ML-VRT) gave a better visual result in 10 of the 11 cases than when using a transfer function not adapting to signal intensity variations.

  • 294.
    Ovrén, Hannes
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Continuous Models for Cameras and Inertial Sensors2018Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [sv]

    Att använda bilder för att återskapa världen omkring oss i tre dimensioner är ett klassiskt problem inom datorseende. Några exempel på användningsområden är inom navigering och kartering för autonoma system, stadsplanering och specialeffekter för film och spel. En vanlig metod för 3D-rekonstruktion är det som kallas ”struktur från rörelse”. Namnet kommer sig av att man avbildar (fotograferar) en miljö från flera olika platser, till exempel genom att flytta kameran. Det är därför något ironiskt att många struktur-från-rörelse-algoritmer får problem om kameran inte är stilla när bilderna tas, exempelvis genom att använda sig av ett stativ. Anledningen är att en kamera i rörelse ger upphov till störningar i bilden vilket ger sämre bildmätningar, och därmed en sämre 3D-rekonstruktion. Ett välkänt exempel är rörelseoskärpa, medan ett annat är kopplat till användandet av en elektronisk rullande slutare. I en kamera med rullande slutare avbildas inte alla pixlar i bilden samtidigt, utan istället rad för rad. Om kameran rör på sig medan bilden tas uppstår därför störningar i bilden som måste tas om hand om för att få en bra rekonstruktion.

    Den här avhandlingen berör robusta metoder för 3D-rekonstruktion med rörliga kameror. En röd tråd inom arbetet är användandet av en tröghetssensor (IMU). En IMU mäter vinkelhastigheter och accelerationer, och dessa mätningar kan användas för att bestämma hur kameran har rört sig över tid. Kunskap om kamerans rörelse ger möjlighet att korrigera för störningar på grund av den rullande slutaren. Ytterligare en fördel med en IMU är att den ger mätningar även i de fall då en kamera inte kan göra det. Exempel på sådana fall är vid extrem rörelseoskärpa, starkt motljus, eller om det saknas struktur i bilden.

    Om man vill använda en kamera tillsammans med en IMU så måste dessa kalibreras och synkroniseras: relationen mellan deras respektive koordinatsystem måste bestämmas, och de måste vara överens om vad klockan är. I den här avhandlingen presenteras en metod för att automatiskt kalibrera och synkronisera ett kamera-IMU-system utan krav på exempelvis kalibreringsobjekt eller speciella rörelsemönster.

    I klassisk struktur från rörelse representeras kamerans rörelse av att varje bild beskrivs med en kamera-pose. Om man istället representerar kamerarörelsen som en tidskontinuerlig trajektoria kan man på ett naturligt sätt hantera problematiken kring rullande slutare. Det gör det också enkelt att införa tröghetsmätningar från en IMU. En tidskontinuerlig kameratrajektoria kan skapas på flera sätt, men en vanlig metod är att använda sig av så kallade splines. Förmågan hos en spline att representera den faktiska kamerarörelsen beror på hur tätt dess knutar placeras. Den här avhandlingen presenterar en metod för att uppskatta det approximationsfel som uppkommer vid valet av en för gles spline. Det uppskattade approximationsfelet kan sedan användas för att balansera mätningar från kameran och IMU:n när dessa används för sensorfusion. Avhandlingen innehåller också en metod för att bestämma hur tät en spline behöver vara för att ge ett gott resultat.

    En annan metod för 3D-rekonstruktion är att använda en kamera som också mäter djup, eller avstånd. Vissa djupkameror, till exempel Microsoft Kinect, har samma problematik med rullande slutare som vanliga kameror. I den här avhandlingen visas hur den rullande slutaren i kombination med olika typer och storlekar av rörelser påverkar den återskapade 3D-modellen. Genom att använda tröghetsmätningar från en IMU kan djupbilderna korrigeras, vilket visar sig ge en bättre 3D-modell.

    Delarbeten
    1. Improving RGB-D Scene Reconstruction using Rolling Shutter Rectification
    Öppna denna publikation i ny flik eller fönster >>Improving RGB-D Scene Reconstruction using Rolling Shutter Rectification
    2015 (Engelska)Ingår i: New Development in Robot Vision / [ed] Yu Sun, Aman Behal & Chi-Kit Ronald Chung, Springer Berlin/Heidelberg, 2015, s. 55-71Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    Scene reconstruction, i.e. the process of creating a 3D representation (mesh) of some real world scene, has recently become easier with the advent of cheap RGB-D sensors (e.g. the Microsoft Kinect).

    Many such sensors use rolling shutter cameras, which produce geometrically distorted images when they are moving. To mitigate these rolling shutter distortions we propose a method that uses an attached gyroscope to rectify the depth scans.We also present a simple scheme to calibrate the relative pose and time synchronization between the gyro and a rolling shutter RGB-D sensor.

    For scene reconstruction we use the Kinect Fusion algorithm to produce meshes. We create meshes from both raw and rectified depth scans, and these are then compared to a ground truth mesh. The types of motion we investigate are: pan, tilt and wobble (shaking) motions.

    As our method relies on gyroscope readings, the amount of computations required is negligible compared to the cost of running Kinect Fusion.

    This chapter is an extension of a paper at the IEEE Workshop on Robot Vision [10]. Compared to that paper, we have improved the rectification to also correct for lens distortion, and use a coarse-to-fine search to find the time shift more quicky.We have extended our experiments to also investigate the effects of lens distortion, and to use more accurate ground truth. The experiments demonstrate that correction of rolling shutter effects yields a larger improvement of the 3D model than correction for lens distortion.

    Ort, förlag, år, upplaga, sidor
    Springer Berlin/Heidelberg, 2015
    Serie
    Cognitive Systems Monographs, ISSN 1867-4925 ; 23
    Nationell ämneskategori
    Datorseende och robotik (autonoma system)
    Identifikatorer
    urn:nbn:se:liu:diva-114344 (URN)10.1007/978-3-662-43859-6_4 (DOI)978-3-662-43858-9 (ISBN)978-3-662-43859-6 (ISBN)
    Projekt
    Learnable Camera Motion Models
    Tillgänglig från: 2015-02-19 Skapad: 2015-02-19 Senast uppdaterad: 2018-06-19Bibliografiskt granskad
    2. Gyroscope-based video stabilisation with auto-calibration
    Öppna denna publikation i ny flik eller fönster >>Gyroscope-based video stabilisation with auto-calibration
    2015 (Engelska)Ingår i: 2015 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2015, s. 2090-2097Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    We propose a technique for joint calibration of a wide-angle rolling shutter camera (e.g. a GoPro) and an externally mounted gyroscope. The calibrated parameters are time scaling and offset, relative pose between gyroscope and camera, and gyroscope bias. The parameters are found using non-linear least squares minimisation using the symmetric transfer error as cost function. The primary contribution is methods for robust initialisation of the relative pose and time offset, which are essential for convergence. We also introduce a robust error norm to handle outliers. This results in a technique that works with general video content and does not require any specific setup or calibration patterns. We apply our method to stabilisation of videos recorded by a rolling shutter camera, with a rigidly attached gyroscope. After recording, the gyroscope and camera are jointly calibrated using the recorded video itself. The recorded video can then be stabilised using the calibrated parameters. We evaluate the technique on video sequences with varying difficulty and motion frequency content. The experiments demonstrate that our method can be used to produce high quality stabilised videos even under difficult conditions, and that the proposed initialisation is shown to end up within the basin of attraction. We also show that a residual based on the symmetric transfer error is more accurate than residuals based on the recently proposed epipolar plane normal coplanarity constraint.

    Serie
    IEEE International Conference on Robotics and Automation ICRA, ISSN 1050-4729
    Nyckelord
    Calibration, Cameras, Cost function, Gyroscopes, Robustness, Synchronization
    Nationell ämneskategori
    Elektroteknik och elektronik Signalbehandling
    Identifikatorer
    urn:nbn:se:liu:diva-120182 (URN)10.1109/ICRA.2015.7139474 (DOI)000370974902014 ()978-1-4799-6922-7; 978-1-4799-6923-4 (ISBN)
    Konferens
    2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 26-30 May, 2015
    Projekt
    LCMMVPS
    Forskningsfinansiär
    Vetenskapsrådet, 2014-5928Stiftelsen för strategisk forskning (SSF), IIS11-0081
    Tillgänglig från: 2015-07-13 Skapad: 2015-07-13 Senast uppdaterad: 2018-06-19Bibliografiskt granskad
    3. Spline Error Weighting for Robust Visual-Inertial Fusion
    Öppna denna publikation i ny flik eller fönster >>Spline Error Weighting for Robust Visual-Inertial Fusion
    2018 (Engelska)Ingår i: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018, s. 321-329Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    In this paper we derive and test a probability-based weighting that can balance residuals of different types in spline fitting. In contrast to previous formulations, the proposed spline error weighting scheme also incorporates a prediction of the approximation error of the spline fit. We demonstrate the effectiveness of the prediction in a synthetic experiment, and apply it to visual-inertial fusion on rolling shutter cameras. This results in a method that can estimate 3D structure with metric scale on generic first-person videos. We also propose a quality measure for spline fitting, that can be used to automatically select the knot spacing. Experiments verify that the obtained trajectory quality corresponds well with the requested quality. Finally, by linearly scaling the weights, we show that the proposed spline error weighting minimizes the estimation errors on real sequences, in terms of scale and end-point errors.

    Serie
    Computer Vision and Pattern Recognition, ISSN 1063-6919
    Nationell ämneskategori
    Elektroteknik och elektronik
    Identifikatorer
    urn:nbn:se:liu:diva-149495 (URN)10.1109/CVPR.2018.00041 (DOI)000457843600034 ()978-1-5386-6420-9 (ISBN)978-1-5386-6421-6 (ISBN)
    Konferens
    The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 18-22, 2018, Salt Lake City, USA
    Forskningsfinansiär
    Vetenskapsrådet, 2014-5928Vetenskapsrådet, 2014-6227
    Tillgänglig från: 2018-07-03 Skapad: 2018-07-03 Senast uppdaterad: 2019-02-26Bibliografiskt granskad
  • 295.
    Ovrén, Hannes
    et al.
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska högskolan.
    Forssén, Per-Erik
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska högskolan.
    Törnqvist, David
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Improving RGB-D Scene Reconstruction using Rolling Shutter Rectification2015Ingår i: New Development in Robot Vision / [ed] Yu Sun, Aman Behal & Chi-Kit Ronald Chung, Springer Berlin/Heidelberg, 2015, s. 55-71Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    Scene reconstruction, i.e. the process of creating a 3D representation (mesh) of some real world scene, has recently become easier with the advent of cheap RGB-D sensors (e.g. the Microsoft Kinect).

    Many such sensors use rolling shutter cameras, which produce geometrically distorted images when they are moving. To mitigate these rolling shutter distortions we propose a method that uses an attached gyroscope to rectify the depth scans.We also present a simple scheme to calibrate the relative pose and time synchronization between the gyro and a rolling shutter RGB-D sensor.

    For scene reconstruction we use the Kinect Fusion algorithm to produce meshes. We create meshes from both raw and rectified depth scans, and these are then compared to a ground truth mesh. The types of motion we investigate are: pan, tilt and wobble (shaking) motions.

    As our method relies on gyroscope readings, the amount of computations required is negligible compared to the cost of running Kinect Fusion.

    This chapter is an extension of a paper at the IEEE Workshop on Robot Vision [10]. Compared to that paper, we have improved the rectification to also correct for lens distortion, and use a coarse-to-fine search to find the time shift more quicky.We have extended our experiments to also investigate the effects of lens distortion, and to use more accurate ground truth. The experiments demonstrate that correction of rolling shutter effects yields a larger improvement of the 3D model than correction for lens distortion.

  • 296.
    Park, Sung
    et al.
    University of California, Davis, USA.
    Yu, Hongfeng
    University of California, Davis, USA.
    Hotz, Ingrid
    University of California, Davis, USA.
    Linsen, Lars
    Ernst-Moritz-Arndt-Universität Greifswald Greifswald, Germany.
    Hamann, Bernd
    University of California, Davis, USA.
    Structure-accentuating Dense Flow Visualization2006Konferensbidrag (Refereegranskat)
    Abstract [en]

    Vector field visualization approaches can broadly be categorized into approaches that directly visualize local orintegrated flow and approaches that analyze the topological structure and visualize extracted features. Our goal was to come up with a method that falls into the first category, yet brings out structural information. We have developed a dense flow visualization method that shows the overall flow behavior while accentuating structural information without performing a topological analysis. Our method is based on a geometry-based flow integration step and a texture-based visual exploration step. The flow integration step generates a density field, which is written into a texture. The density field is generated by tracing particles under the influence of the underlying vector field.When using a quasi-random seeding strategy for initialization, the resulting density is high in attracting regions and low in repelling regions. Density is measured by the number of particles per region accumulated over time. We generate one density field using forward and one using backward propagation. The density fields are explored using texture-based rendering techniques. We generate the two output images separately and blend the results, which allows us to distinguish between inflow and outflow regions. We obtained dense flow visualizations that display the overall flow behavior, emphasize critical and separating regions, and indicate flow direction in the neighborhood of these regions. We analyzed the results of our method for isolated first-order singularities and real data sets.

  • 297.
    Pedrosa, Joao
    et al.
    Katholieke University of Leuven, Belgium.
    Heyde, Brecht
    Katholieke University of Leuven, Belgium.
    Heeren, Laurens
    Katholieke University of Leuven, Belgium.
    Engvall, Jan
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Medicinska fakulteten. Region Östergötland, Hjärt- och Medicincentrum, Fysiologiska kliniken US. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Zamorano, Jose
    Ramon and Cajal University Hospital, Spain.
    Papachristidis, Alexandros
    Kings Coll Hospital London, England.
    Edvardsen, Thor
    Oslo University Hospital, Norway; Oslo University Hospital, Norway.
    Claus, Piet
    Katholieke University of Leuven, Belgium.
    Dhooge, Jan
    Katholieke University of Leuven, Belgium.
    Automatic Short Axis Orientation of the Left Ventricle in 3D Ultrasound Recordings2016Ingår i: MEDICAL IMAGING 2016: ULTRASONIC IMAGING AND TOMOGRAPHY, SPIE-INT SOC OPTICAL ENGINEERING , 2016, Vol. 9790, nr 97900EKonferensbidrag (Refereegranskat)
    Abstract [en]

    The recent advent of three-dimensional echocardiography has led to an increased interest from the scientific community in left ventricle segmentation frameworks for cardiac volume and function assessment. An automatic orientation of the segmented left ventricular mesh is an important step to obtain a point-to-point correspondence between the mesh and the cardiac anatomy. Furthermore, this would allow for an automatic division of the left ventricle into the standard 17 segments and, thus, fully automatic per-segment analysis, e.g. regional strain assessment. In this work, a method for fully automatic short axis orientation of the segmented left ventricle is presented. The proposed framework aims at detecting the inferior right ventricular insertion point. 211 three-dimensional echocardiographic images were used to validate this framework by comparison to manual annotation of the inferior right ventricular insertion point. A mean unsigned error of 8, 05 degrees +/- 18, 50 degrees was found, whereas the mean signed error was 1, 09 degrees. Large deviations between the manual and automatic annotations (amp;gt; 30 degrees) only occurred in 3, 79% of cases. The average computation time was 666ms in a non-optimized MATLAB environment, which potentiates real-time application. In conclusion, a successful automatic real-time method for orientation of the segmented left ventricle is proposed.

  • 298.
    Pedrosa, Joao
    et al.
    Katholieke University of Leuven, Belgium.
    Queiros, Sandro
    Katholieke University of Leuven, Belgium; University of Minho, Portugal; University of Minho, Portugal.
    Bernard, Olivier
    University of Lyon 1, France.
    Engvall, Jan
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Medicinska fakulteten. Region Östergötland, Hjärt- och Medicincentrum, Fysiologiska kliniken US.
    Edvardsen, Thor
    University of Oslo, Norway; Oslo University Hospital, Norway.
    Nagel, Eike
    University Hospital Frankfurt Main, Germany.
    Dhooge, Jan
    Katholieke University of Leuven, Belgium.
    Fast and Fully Automatic Left Ventricular Segmentation and Tracking in Echocardiography Using Shape-Based B-Spline Explicit Active Surfaces2017Ingår i: IEEE Transactions on Medical Imaging, ISSN 0278-0062, E-ISSN 1558-254X, Vol. 36, nr 11, s. 2287-2296Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Cardiac volume/function assessment remains a critical step in daily cardiology, and 3-D ultrasound plays an increasingly important role. Fully automatic left ventricular segmentation is, however, a challenging task due to the artifacts and low contrast-to-noise ratio of ultrasound imaging. In this paper, a fast and fully automatic framework for the full-cycle endocardial left ventricle segmentation is proposed. This approach couples the advantages of the B-spline explicit active surfaces framework, a purely image information approach, to those of statistical shape models to give prior information about the expected shape for an accurate segmentation. The segmentation is propagated throughout the heart cycle using a localized anatomical affine optical flow. It is shown that this approach not only outperforms other state-of-the-art methods in terms of distance metrics with a mean average distances of 1.81 +/- 0.59 and 1.98 +/- 0.66 mm at end-diastole and end-systole, respectively, but is computationally efficient (in average 11 s per 4-D image) and fully automatic.

  • 299.
    Persson, Mikael
    et al.
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Piccini, Tommaso
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Felsberg, Michael
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Mester, Rudolf
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten. Frankfurt University, Germany.
    Robust Stereo Visual Odometry from Monocular Techniques2015Ingår i: 2015 IEEE Intelligent Vehicles Symposium (IV), Institute of Electrical and Electronics Engineers (IEEE), 2015, s. 686-691Konferensbidrag (Refereegranskat)
    Abstract [en]

    Visual odometry is one of the most active topics in computer vision. The automotive industry is particularly interested in this field due to the appeal of achieving a high degree of accuracy with inexpensive sensors such as cameras. The best results on this task are currently achieved by systems based on a calibrated stereo camera rig, whereas monocular systems are generally lagging behind in terms of performance. We hypothesise that this is due to stereo visual odometry being an inherently easier problem, rather than than due to higher quality of the state of the art stereo based algorithms. Under this hypothesis, techniques developed for monocular visual odometry systems would be, in general, more refined and robust since they have to deal with an intrinsically more difficult problem. In this work we present a novel stereo visual odometry system for automotive applications based on advanced monocular techniques. We show that the generalization of these techniques to the stereo case result in a significant improvement of the robustness and accuracy of stereo based visual odometry. We support our claims by the system results on the well known KITTI benchmark, achieving the top rank for visual only systems∗ .

  • 300.
    Pettersson, Erik
    Linköpings universitet, Institutionen för systemteknik.
    Signal- och bildbehandling på moderna grafikprocessorer2005Självständigt arbete på grundnivå (yrkesexamen), 20 poäng / 30 hpStudentuppsats
    Abstract [sv]

    En modern grafikprocessor är oerhört kraftfull och har en prestanda som potentiellt sett är många gånger högre än för en modern mikroprocessor. I takt med att grafikprocessorn blivit alltmer programmerbar har det blivit möjligt att använda den för beräkningstunga tillämpningar utanför dess normala användningsområde. Inom det här arbetet utreds vilka möjligheter och begränsningar som uppstår vid användandet av grafikprocessorer för generell programmering. Arbetet inriktas främst mot signal- och bildbehandlingstillämpningar men mycket av principerna är tillämpliga även inom andra områden.

    Ett ramverk för bildbehandling implementeras och några algoritmer inom bildanalys realiseras och utvärderas, bland annat stereoseende och beräkning av optiskt flöde. Resultaten visar på att vissa tillämpningar kan uppvisa en avsevärd prestandaökning i en grafikprocessor jämfört med i en mikroprocessor men att andra tillämpningar kan vara ineffektiva eller mycket svåra att implementera.

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