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  • 151.
    Henrysson, Anders
    et al.
    Linköping University, Department of Science and Technology, Visual Information Technology and Applications (VITA). Linköping University, The Institute of Technology.
    Billinghurst, Mark
    University of Canterbury, Christchurch, New Zealand.
    Using a Mobile Phone for 6DOF Mesh Editing2007In: Proceedings of the 7th ACM SIGCHI New Zealand Chapter's international Conference on Computer-Human interaction: Design Centered HCI., 2007, p. 9-16Chapter in book (Other academic)
    Abstract [en]

    This paper describes how a mobile phone can be used as a six degree of freedom interaction device for 3D mesh editing. Using a video see-through Augmented Reality approach, the mobile phone meets several design guidelines for a natural, easy to learn, 3D human computer interaction device. We have developed a system that allows a user to select one or more vertices in an arbitrary sized polygon mesh and freely translate and rotate them by translating and rotating the device itself. The mesh is registered in 3D and viewed through the device and hence the system provides a unified perception-action space. We present the implementation details and discuss the possible advantages and disadvantages of this approach.

  • 152.
    Henrysson, Anders
    et al.
    Linköping University, Department of Science and Technology, Visual Information Technology and Applications (VITA). Linköping University, The Institute of Technology.
    Marshall, Joe
    University of Nottingham.
    Billinghurst, Mark
    University of Canterbury, Christchurch, New Zealand.
    Experiments in 3D Interaction for Mobile Phone AR2007In: Proceedings of the 5th international conference on Computer graphics and interactive techniques in Australia and Southeast Asia, Perth, Australia, New York: The Association for Computing Machinery, Inc. , 2007, p. 187-194Chapter in book (Other academic)
    Abstract [en]

    In this paper we present an evaluation of several different techniques for virtual object positioning and rotation on a mobile phone. We compare gesture input captured by the phone's front camera, to tangible input, keypad interaction and phone tilting in increasingly complex positioning and rotation tasks in an AR context. Usability experiments found that tangible input techniques are best for translation tasks, while keypad input is best for rotation tasks. Implications for the design of mobile phone 3D interfaces are presented as well as directions for future research.

  • 153.
    Hermosilla, P.
    et al.
    Ulm Univ, Germany.
    Maisch, S.
    Ulm Univ, Germany.
    Ritschel, T.
    UCL, England.
    Ropinski, Timo
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Ulm Univ, Germany.
    Deep-learning the Latent Space of Light Transport2019In: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659, Vol. 38, no 4, p. 207-217Article in journal (Refereed)
    Abstract [en]

    We suggest a method to directly deep-learn light transport, i. e., the mapping from a 3D geometry-illumination-material configuration to a shaded 2D image. While many previous learning methods have employed 2D convolutional neural networks applied to images, we show for the first time that light transport can be learned directly in 3D. The benefit of 3D over 2D is, that the former can also correctly capture illumination effects related to occluded and/or semi-transparent geometry. To learn 3D light transport, we represent the 3D scene as an unstructured 3D point cloud, which is later, during rendering, projected to the 2D output image. Thus, we suggest a two-stage operator comprising a 3D network that first transforms the point cloud into a latent representation, which is later on projected to the 2D output image using a dedicated 3D-2D network in a second step. We will show that our approach results in improved quality in terms of temporal coherence while retaining most of the computational efficiency of common 2D methods. As a consequence, the proposed two stage-operator serves as a valuable extension to modern deferred shading approaches.

  • 154.
    Holmer, Stefan
    Linköping University, Department of Electrical Engineering.
    Implementation and evaluation of content-aware video retargeting techniques2008Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The purpose of this master thesis was to study different content-aware video retargeting techniques, concentrating on a generalization of seam carving for video. Focus have also been put on the possibility to combine different techniques to achieve better retargeting of both multi-shot video and single-shot video. This also involved significant studies of automatic cut detection and different measures of video content. The work resulted in a prototype application for semi-automatic video retargeting, developed in Matlab. Three different retargeting techniques, seam carving, automated pan & scan and subsampling using bi-cubic interpolation, have been implemented in the prototype. The techniques have been evaluated and compared to each other from a content preservation perspective and a perceived quality perspective.

  • 155.
    Holmquist, Karl
    et al.
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Senel, Oeniz
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Felsberg, Michael
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Computing a Collision-Free Path using the monogenic scale space2018In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, 2018, p. 8097-8102Conference paper (Refereed)
    Abstract [en]

    Mobile robots have been used for various purposes with different functionalities which require them to freely move in environments containing both static and dynamic obstacles to accomplish given tasks. One of the most relevant capabilities in terms of navigating a mobile robot in such an environment is to find a safe path to a goal position. This paper shows that there exists an accurate solution to the Laplace equation which allows finding a collision-free path and that it can be efficiently calculated for a rectangular bounded domain such as a map which is represented as an image. This is accomplished by the use of the monogenic scale space resulting in a vector field which describes the attracting and repelling forces from the obstacles and the goal. The method is shown to work in reasonably convex domains and by the use of tessellation of the environment map for non-convex environments.

  • 156.
    Horney, Tobias
    et al.
    Swedish Defence Research Agency, Sweden.
    Ahlberg, Jörgen
    Swedish Defence Research Agency, Sweden.
    Grönwall, Christina
    Swedish Defence Research Agency, Sweden.
    Folkesson, Martin
    Swedish Defence Research Agency, Sweden.
    Silvervarg, Karin
    Swedish Defence Research Agency, Sweden.
    Fransson, Jörgen
    Swedish Defence Research Agency, Sweden.
    Klasén, Lena
    Swedish Defence Research Agency, Sweden.
    Jungert, Erland
    Swedish Defence Research Agency, Sweden.
    Lantz, Fredrik
    Swedish Defence Research Agency, Sweden.
    Ulvklo, Morgan
    Swedish Defence Research Agency, Sweden.
    An information system for target recognition2004In: Volume 5434 Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications / [ed] Belur V. Dasarathy, SPIE - International Society for Optical Engineering, 2004, p. 163-175Conference paper (Refereed)
    Abstract [en]

    We present an approach to a general decision support system. The aim is to cover the complete process for automatic target recognition, from sensor data to the user interface. The approach is based on a query-based information system, and include tasks like feature extraction from sensor data, data association, data fusion and situation analysis. Currently, we are working with data from laser radar, infrared cameras, and visual cameras, studying target recognition from cooperating sensors on one or several platforms. The sensors are typically airborne and at low altitude. The processing of sensor data is performed in two steps. First, several attributes are estimated from the (unknown but detected) target. The attributes include orientation, size, speed, temperature etc. These estimates are used to select the models of interest in the matching step, where the target is matched with a number of target models, returning a likelihood value for each model. Several methods and sensor data types are used in both steps. The user communicates with the system via a visual user interface, where, for instance, the user can mark an area on a map and ask for hostile vehicles in the chosen area. The user input is converted to a query in ΣQL, a query language developed for this type of applications, and an ontological system decides which algorithms should be invoked and which sensor data should be used. The output from the sensors is fused by a fusion module and answers are given back to the user. The user does not need to have any detailed technical knowledge about the sensors (or which sensors that are available), and new sensors and algorithms can easily be plugged into the system.

  • 157.
    Hotz, Ingrid
    et al.
    University of California, Davis, USA.
    Feng, Louis
    University of California, Davis, USA.
    Hagen, Hans
    University of Kaiserslautern.
    Hamann, Bernd
    University of California, Davis, USA.
    Joy, Ken
    University of California, Davis, USA.
    Tensor Field Visualization Using a Metric Interpretation2006In: Visualization and Image Processing of Tensor Fields / [ed] Joachim Weickert, Hans Hagen, Springer, 2006, p. 269-281Chapter in book (Refereed)
    Abstract [en]

    This chapter introduces a visualization method specifically tailored to the class of tensor fields with properties similar to stress and strain tensors. Such tensor fields play an important role in many application areas such as structure mechanics or solid state physics. The presented technique is a global method that represents the physical meaning of these tensor fields with their central features: regions of compression or expansion. The method consists of two steps: first, the tensor field is interpreted as a distortion of a flat metric with the same topological structure; second, the resulting metric is visualized using a texture-based approach. The method supports an intuitive distinction between positive and negative eigenvalues.

  • 158.
    Hotz, Ingrid
    et al.
    Universtiy of California,Davis, USA.
    Feng, Louis
    Universtiy of California,Davis, USA.
    Hagen, Hans
    University of Kaiserslautern,Germany.
    Hamann, Bernd
    University of California, Davis, USA.
    Joy, Ken
    University of California, Davis, USA.
    Jeremic, Boris
    University of California, Davis, USA.
    Physically Based Methods for Tensor Field Visualization2004Conference paper (Refereed)
    Abstract [en]

    The physical interpretation of mathematical features of tensor fields is highly application-specific. Existing visualization methods for tensor fields only cover a fraction of the broad application areas. We present a visualization method tailored specifically to the class of tensor field exhibiting properties similar to stress and strain tensors, which are commonly encountered in geomechanics. Our technique is a global method that represents the physical meaning of these tensor fields with their central features: regions of compression or expansion. The method is based on two steps: first, we define a positive definite metric, with the same topological structure as the tensor field; second, we visualize the resulting metric. The eigenvector fields are represented using a texture-based approach resembling line integral convolution (LIC) methods. The eigenvalues of the metric are encoded in free parameters of the texture definition. Our method supports an intuitive distinction between positive and negative eigenvalues. We have applied our method to synthetic and some standard data sets, and "real" data from earth science and mechanical engineering application.

  • 159.
    Hotz, Ingrid
    et al.
    Universtiy of California, Davis.
    Feng, Louis
    University of California, Davis.
    Hamann, Bernd
    University of California, Davis, USA.
    Joy, Ken
    University of California, Davis, USA.
    Tensor-fields Visualization using a Fabric like Texture on Arbitrary two-dimensional Surfaces2009In: Mathematical Foundations of Scientific Visualization / [ed] Torsten Möller,Bernd Hamann,Robert D. Russell, Springer, 2009, p. 139-155Chapter in book (Refereed)
    Abstract [en]

    We present a visualization method that for three-dimensional tensor fields based on the idea of a stretched or compressed piece of fabric used as a “texture” for a two-dimensional surfaces. The texture parameters as the fabric density reflect the physical properties of the tensor field. This method is especially appropriate for the visualization of stress and strain tensor fields that play an important role in many application areas including mechanics and solid state physics. To allow an investigation of a three-dimensional field we use a scalar field that defines a one-parameter family of iso-surfaces controlled by their iso-value. This scalar-field can be a “connected” scalar field, for example, pressure or an additional scalar field representing some symmetry or inherent structure of the dataset. Texture generation consists basically of three steps. The first is the transformation of the tensor field into a positive definite metric. The second step is the generation of an input for the final texture generation using line integral convolution (LIC). This input image consists of “bubbles” whose shape and density are controlled by the eigenvalues of the tensor field. This spot image incorporates the entire information content defined by the three eigenvalue fields. Convolving this input texture in direction of the eigenvector fields provides a continuous representation. This method supports an intuitive distinction between positive and negative eigenvalues and supports the additional visualization of a connected scalar field.

  • 160.
    Hotz, Ingrid
    et al.
    University of Kaiserslautern.
    Hagen, Hans
    University of Kaiserslautern.
    Isometric Embedding for a Discrete Metric2004In: Geometric Modeling for Scientific Visualization / [ed] Guido Brunnett ,Bernd Hamann,Heinrich Müller ,Lars Linsen, Springer, 2004, 1, p. 19-36Chapter in book (Refereed)
  • 161.
    Hotz, Ingrid
    et al.
    Zuse Institute Berlin, Berlin, Germany.
    Peikert, Ronald
    ETH Zurich, Zurich, Switzerland .
    Definition  of  a  Multifield2014In: Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization / [ed] Charles D. Hansen; Min Chen; Christopher R. Johnson; Arie E. Kaufman; Hans Hagen, Springer London, 2014, p. 105-109Chapter in book (Refereed)
    Abstract [en]

    A challenge, visualization is often faced with, is the complex structure of scientific data. Complexity can arise in various ways, from high dimensionalities of domains and ranges, time series of measurements, ensemble simulations, to heterogeneous collections of data, such as combinations of measured and simulated data. Many of these complexities can be subsumed under a concept of multifields, and in fact, multifield visualization has been identified as one of the major current challenges in scientific visualization. In this chapter, we propose a multifield definition, which will allow us a systematic approach to discussing related research.

  • 162.
    Hotz, Ingrid
    et al.
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
    Schultz, ThomasUniversity Bonn, Germany.
    Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data (Dagstuhl’14)2015Collection (editor) (Refereed)
    Abstract [en]
    • Transfer result from one application to another between which there is otherwise not much exchange
    • Bringing together ideas from applications and theory: Applications can stimulate new basic research, as basic results can be of great use in the applications
    • Summarizing the state of the art and major open questions in the field
    • Presenting new and innovative work with the capabilities of advancing the field
  • 163.
    Hotz, Ingrid
    et al.
    University of California, USA.
    Sreevalsan-Nair, Jaya
    University of California, USA.
    Hagen, Hans
    Technical University of Kaiserslautern,Kaiserslautern, Germany.
    Hamann, Bernd
    University of California, USA.
    Tensor Field Reconstruction Based on Eigenvector and Eigenvalue Interpolation2010In: Dagstuhl Follow-Ups, E-ISSN 1868-8977, Vol. 1, p. 110-123Article in journal (Refereed)
    Abstract [en]

    Interpolation is an essential step in the visualization process. While most data from simulations or experiments are discrete many visualization methods are based on smooth, continuous data approximation or interpolation methods. We introduce a new interpolation method for symmetrical tensor fields given on a triangulated domain. Differently from standard tensor field interpolation, which is based on the tensor components, we use tensor invariants, eigenvectors and eigenvalues, for the interpolation. This interpolation minimizes the number of eigenvectors and eigenvalues computations by restricting it to mesh vertices and makes an exact integration of the tensor lines possible. The tensor field topology is qualitatively the same as for the component wise-interpolation. Since the interpolation decouples the “shape” and “direction” interpolation it is shape-preserving, what is especially important for tracing fibers in diffusion MRI data.

  • 164.
    Hultberg, Johanna
    Linköping University, Department of Electrical Engineering, Computer Vision.
    Dehazing of Satellite Images2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The aim of this work is to find a method for removing haze from satellite imagery. This is done by taking two algorithms developed for images taken from the sur- face of the earth and adapting them for satellite images. The two algorithms are Single Image Haze Removal Using Dark Channel Prior by He et al. and Color Im- age Dehazing Using the Near-Infrared by Schaul et al. Both algorithms, altered to fit satellite images, plus the combination are applied on four sets of satellite images. The results are compared with each other and the unaltered images. The evaluation is both qualitative, i.e. looking at the images, and quantitative using three properties: colorfulness, contrast and saturated pixels. Both the qualitative and the quantitative evaluation determined that using only the altered version of Dark Channel Prior gives the result with the least amount of haze and whose colors look most like reality. 

  • 165.
    Häger, Gustav
    Linköping University, Department of Electrical Engineering, Computer Vision.
    Improving Discriminative Correlation Filters for Visual Tracking2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Generic visual tracking is one of the classical problems in computer vision. In this problem, no prior knowledge of the target is available aside from a bounding box in the initial frame of the sequence. The generic visual tracking is a difficult task due to a number of factors such as momentary occlusions, target rotations, changes in target illumination and variations in the target size. In recent years, discriminative correlation filter (DCF) based trackers have shown promising results for visual tracking. These DCF based methods use the Fourier transform to efficiently calculate detection and model updates, allowing significantly higher frame rates than competing methods. However, existing DCF based methods only estimate translation of the object while ignoring changes in size.This thesis investigates the problem of accurately estimating the scale variations within a DCF based framework. A novel scale estimation method is proposed by explicitly constructing translation and scale filters. The proposed scale estimation technique is robust and significantly improve the tracking performance, while operating at real-time. In addition, a comprehensive evaluation of feature representations in a DCF framework is performed. Experiments are performed on the benchmark OTB-2015 dataset, as well as the VOT 2014 dataset. The proposed methods are shown to significantly improve the performance of existing DCF based trackers.

  • 166.
    Häger, Gustav
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Computer Vision.
    Bhat, Goutam
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Computer Vision.
    Danelljan, Martin
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Computer Vision.
    Khan, Fahad Shahbaz
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Computer Vision.
    Felsberg, Michael
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Computer Vision.
    Rudol, Piotr
    Linköping University, The Institute of Technology.
    Doherty, Patrick
    Linköping University, The Institute of Technology.
    Combining Visual Tracking and Person Detection for Long Term Tracking on a UAV2016In: Proceedings of the 12th International Symposium on Advances in Visual Computing, 2016Conference paper (Refereed)
    Abstract [en]

    Visual object tracking performance has improved significantly in recent years. Most trackers are based on either of two paradigms: online learning of an appearance model or the use of a pre-trained object detector. Methods based on online learning provide high accuracy, but are prone to model drift. The model drift occurs when the tracker fails to correctly estimate the tracked object’s position. Methods based on a detector on the other hand typically have good long-term robustness, but reduced accuracy compared to online methods.

    Despite the complementarity of the aforementioned approaches, the problem of fusing them into a single framework is largely unexplored. In this paper, we propose a novel fusion between an online tracker and a pre-trained detector for tracking humans from a UAV. The system operates at real-time on a UAV platform. In addition we present a novel dataset for long-term tracking in a UAV setting, that includes scenarios that are typically not well represented in standard visual tracking datasets.

  • 167.
    Ingemars, Nils
    Linköping University, Department of Electrical Engineering.
    A feature based face tracker using extended Kalman filtering2007Independent thesis Basic level (professional degree), 20 points / 30 hpStudent thesis
    Abstract [en]

    A face tracker is exactly what it sounds like. It tracks a face in a video sequence. Depending on the complexity of the tracker, it could track the face as a rigid object or as a complete deformable face model with face expressions.

    This report is based on the work of a real time feature based face tracker. Feature based means that you track certain features in the face, like points with special characteristics. It might be a mouth or eye corner, but theoretically it could be any point. For this tracker, the latter is of interest. Its task is to extract global parameters, i.e. rotation and translation, as well as dynamic facial parameters (expressions) for each frame. It tracks feature points using motion between frames and a textured face model (Candide). It then uses an extended Kalman filter to estimate the parameters from the tracked feature points.

  • 168.
    Ingemars, Nils
    et al.
    Linköping University, Department of Electrical Engineering, Image Coding. Linköping University, The Institute of Technology.
    Ahlberg, Jörgen
    Linköping University, Department of Electrical Engineering, Image Coding. Linköping University, The Institute of Technology.
    Feature-based Face Tracking using Extended Kalman Filtering2007Conference paper (Other academic)
    Abstract [en]

    This work examines the possiblity to, with the computational power of today’s consumer hardware, employ techniques previously developed for 3D tracking of rigid objects, and use them for tracking of deformable objects. Our target objects are human faces in a video conversation pose, and our purpose is to create a deformable face tracker based on a head tracker operating in real-time on consumer hardware. We also investigate how to combine model-based and image based tracking in order to get precise tracking and avoid drift.

  • 169.
    Isoz, Wilhelm
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Calibration of Multispectral Sensors2005Independent thesis Basic level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This thesis describes and evaluates a number of approaches and algorithms for nonuniform correction (NUC) and suppression of fixed pattern noise in a image sequence. The main task for this thesis work was to create a general NUC for infrared focal plane arrays. To create a radiometrically correct NUC, reference based methods using polynomial approximation are used instead of the more common scene based methods which creates a cosmetic NUC.

    The pixels that can not be adjusted to give a correct value for the incomming radiation are defined as dead. Four separate methods of identifying dead pixels are used to find these pixels. Both the scene sequence and calibration data are used in these identifying methods.

    The algorithms and methods have all been tested by using real image sequences. A graphical user interface using the presented algorithms has been created in Matlab to simplify the correction of image sequences. An implementation to convert the corrected values from the images to radiance and temperature is also performed.

  • 170.
    Izquierdo, Milagros
    et al.
    Linköping University, Department of Mathematics, Mathematics and Applied Mathematics. Linköping University, Faculty of Science & Engineering.
    Stokes, Klara
    Högskolan i Skövde.
    Isometric Point-Circle Configurations on Surfaces from Uniform Maps2016In: Springer Proceedings in Mathematics and Statistics, ISSN 2194-1009, Vol. 159, p. 201-212Article in journal (Refereed)
    Abstract [en]

    We embed neighborhood geometries of graphs on surfaces as point-circle configurations. We give examples coming from regular maps on surfaces with a maximum number of automorphisms for their genus, and survey geometric realization of pentagonal geometries coming from Moore graphs. An infinite family of point-circle v4'>v4v4 configurations on p-gonal surfaces with two p-gonal morphisms is given. The image of these configurations on the sphere under the two p-gonal morphisms is also described.

  • 171.
    Jack Lee, Wing
    et al.
    Monash University of Malaysia, Malaysia.
    Ng, Kok Yew
    Linköping University, Department of Electrical Engineering. Monash University of Malaysia, Malaysia.
    Luh Tan, Chin
    Monash University of Malaysia, Malaysia; Trity Technology, Malaysia.
    Pin Tan, Chee
    Monash University of Malaysia, Malaysia; Trity Technology, Malaysia.
    Real-Time Face Detection And Motorized Tracking Using ScicosLab and SMCube On SoCs2016In: 14TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV), IEEE, 2016, article id UNSP Su23.3Conference paper (Refereed)
    Abstract [en]

    This paper presents a method for real-time detection and tracking of the human face. This is achieved using the Raspberry Pi microcomputer and the Easylab microcontroller as the main hardware with a camera mounted on servomotors for continuous image feed-in. Real-time face detection is performed using Haar-feature classifiers and ScicosLab in the Raspberry Pi. Then, the Easylab is responsible for face tracking, keeping the face in the middle of the frame through a pair of servomotors that control the horizontal and vertical movements of the camera. The servomotors are in turn controlled based on the state-diagrams designed using SMCube in the EasyLab. The methodology is verified via practical experimentation.

  • 172.
    Jackman, Simeon
    Linköping University, Department of Biomedical Engineering.
    Football Shot Detection using Convolutional Neural Networks2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In this thesis, three different neural network architectures are investigated to detect the action of a shot within a football game using video data. The first architecture uses con- ventional convolution and pooling layers as feature extraction. It acts as a baseline and gives insight into the challenges faced during shot detection. The second architecture uses a pre-trained feature extractor. The last architecture uses three-dimensional convolution. All these networks are trained using short video clips extracted from football game video streams. Apart from investigating network architectures, different sampling methods are evaluated as well. This thesis shows that amongst the three evaluated methods, the ap- proach using MobileNetV2 as a feature extractor works best. However, when applying the networks to a video stream there are a multitude of challenges, such as false positives and incorrect annotations that inhibit the potential of detecting shots.

  • 173.
    Jackowski, C.
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Wyss, M.
    Department of Preventive, Restorative and Paediatric Dentistry, University of Bern, 3010 Bern, Switzerland.
    Persson, A.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Health Sciences. Linköping University, Department of Medical and Health Sciences, Radiology.
    Classens, M.
    Department of Diagnostic Radiology, Lindenhofspital, Bremgartenstrasse 117, 3001 Bern, Switzerland.
    Thali, M.J.
    Center of Forensic Imaging and Virtopsy, Institute of Forensic Medicine, University of Bern, Bühlstreet 20, 3012 Bern, Switzerland.
    Lussi, A.
    Department of Preventive, Restorative and Paediatric Dentistry, University of Bern, 3010 Bern, Switzerland.
    Ultra-high-resolution dual-source CT for forensic dental visualization - Discrimination of ceramic and composite fillings2008In: International journal of legal medicine (Print), ISSN 0937-9827, E-ISSN 1437-1596, Vol. 122, no 4, p. 301-307Article in journal (Refereed)
    Abstract [en]

    Dental identification is the most valuable method to identify human remains in single cases with major postmortem alterations as well as in mass casualties because of its practicability and demanding reliability. Computed tomography (CT) has been investigated as a supportive tool for forensic identification and has proven to be valuable. It can also scan the dentition of a deceased within minutes. In the present study, we investigated currently used restorative materials using ultra-high-resolution dual-source CT and the extended CT scale for the purpose of a color-encoded, in scale, and artifact-free visualization in 3D volume rendering. In 122 human molars, 220 cavities with 2-, 3-, 4- and 5-mm diameter were prepared. With presently used filling materials (different composites, temporary filling materials, ceramic, and liner), these cavities were restored in six teeth for each material and cavity size (exception amalgam n=1). The teeth were CT scanned and images reconstructed using an extended CT scale. Filling materials were analyzed in terms of resulting Hounsfield units (HU) and filling size representation within the images. Varying restorative materials showed distinctively differing radiopacities allowing for CT-data-based discrimination. Particularly, ceramic and composite fillings could be differentiated. The HU values were used to generate an updated volume-rendering preset for postmortem extended CT scale data of the dentition to easily visualize the position of restorations, the shape (in scale), and the material used which is color encoded in 3D. The results provide the scientific background for the application of 3D volume rendering to visualize the human dentition for forensic identification purposes. © 2008 Springer-Verlag.

  • 174.
    Jankowai, Jochen
    et al.
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
    Wang, Bei
    Univ Utah, UT 84112 USA.
    Hotz, Ingrid
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
    Robust Extraction and Simplification of 2D Symmetric Tensor Field Topology2019In: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659, Vol. 38, no 3, p. 337-349Article in journal (Refereed)
    Abstract [en]

    In this work, we propose a controlled simplification strategy for degenerated points in symmetric 2D tensor fields that is based on the topological notion of robustness. Robustness measures the structural stability of the degenerate points with respect to variation in the underlying field. We consider an entire pipeline for generating a hierarchical set of degenerate points based on their robustness values. Such a pipeline includes the following steps: the stable extraction and classification of degenerate points using an edge labeling algorithm, the computation and assignment of robustness values to the degenerate points, and the construction of a simplification hierarchy. We also discuss the challenges that arise from the discretization and interpolation of real world data.

  • 175.
    Jogbäck, Mats
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Bildbaserad estimering av rörelse för reducering av rörelseartefakter2006Independent thesis Basic level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Before reconstructing a three dimensional volume from an MR brain imaging sequence there is a need for aligning each slice, due to unavoidable movement of the patient during the scanning. This procedure is known as image registration and the method used primarily today is based on a selected slice being the reference slice and then registrating the neighbouring slices, which are assumed to be of minimal deviation.

    The purpose of this thesis is to use another method commonly used in computer vision - to estimate the motion from a regular videosequence, by tracking markers indicating movement. The aim is to create a robust estimation of the movement of the head, which in turn can be used to create a more accurate alignment and volume.

  • 176.
    Johansson, Marcus
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems.
    Online Whole-Body Control using Hierarchical Quadratic Programming: Implementation and Evaluation of the HiQP Control Framework2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The application of local optimal control is a promising paradigm for manipulative robot motion generation.In practice this involves instantaneous formulations of convex optimization problems depending on the current joint configuration of the robot and the environment.To be effective, however, constraints have to be carefully constructed as this kind of motion generation approach has a trade-off of completeness.Local optimal solvers, which are greedy in a temporal sense, have proven to be significantly more effective computationally than classical grid-based or sampling-based planning approaches.

    In this thesis we investigate how a local optimal control approach, namely the task function approach, can be implemented to grant high usability, extendibility and effectivity.This has resulted in the HiQP control framework, which is compatible with ROS, written in C++.The framework supports geometric primitives to aid in task customization by the user.It is also modular as to what communication system it is being used with, and to what optimization library it uses for finding optimal controls.

    We have evaluated the software quality of the framework according to common quantitative methods found in the literature.We have also evaluated an approach to perform tasks using minimal jerk motion generation with promising results.The framework also provides simple translation and rotation tasks based on six rudimentary geometric primitives.Also, task definitions for specific joint position setting, and velocity limitations were implemented.

  • 177.
    Johansson, Victor
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    3D Position Estimation of a Person of Interest in Multiple Video Sequences: Person of Interest Recognition2013Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Because of the increase in the number of security cameras, there is more video footage available than a human could efficiently process. In combination with the fact that computers are getting more efficient, it is getting more and more interesting to solve the problem of detecting and recognizing people automatically.

    Therefore a method is proposed for estimating a 3D-path of a person of interest in multiple, non overlapping, monocular cameras. This project is a collaboration between two master theses. This thesis will focus on recognizing a person of interest from several possible candidates, as well as estimating the 3D-position of a person and providing a graphical user interface for the system. The recognition of the person of interest includes keeping track of said person frame by frame, and identifying said person in video sequences where the person of interest has not been seen before.

    The final product is able to both detect and recognize people in video, as well as estimating their 3D-position relative to the camera. The product is modular and any part can be improved or changed completely, without changing the rest of the product. This results in a highly versatile product which can be tailored for any given situation.

  • 178.
    Johnander, Joakim
    et al.
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Danelljan, Martin
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Khan, Fahad Shahbaz
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Felsberg, Michael
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    DCCO: Towards Deformable Continuous Convolution Operators for Visual Tracking2017In: Computer Analysis of Images and Patterns: 17th International Conference, CAIP 2017, Ystad, Sweden, August 22-24, 2017, Proceedings, Part I / [ed] Michael Felsberg, Anders Heyden and Norbert Krüger, Springer, 2017, Vol. 10424, p. 55-67Conference paper (Refereed)
    Abstract [en]

    Discriminative Correlation Filter (DCF) based methods have shown competitive performance on tracking benchmarks in recent years. Generally, DCF based trackers learn a rigid appearance model of the target. However, this reliance on a single rigid appearance model is insufficient in situations where the target undergoes non-rigid transformations. In this paper, we propose a unified formulation for learning a deformable convolution filter. In our framework, the deformable filter is represented as a linear combination of sub-filters. Both the sub-filter coefficients and their relative locations are inferred jointly in our formulation. Experiments are performed on three challenging tracking benchmarks: OTB-2015, TempleColor and VOT2016. Our approach improves the baseline method, leading to performance comparable to state-of-the-art.

  • 179.
    Jones, Andrew
    et al.
    USC Institute Creat Technology, CA 90094 USA.
    Nagano, Koki
    USC Institute Creat Technology, CA 90094 USA.
    Busch, Jay
    USC Institute Creat Technology, CA 90094 USA.
    Yu, Xueming
    USC Institute Creat Technology, CA 90094 USA.
    Peng, Hsuan-Yueh
    USC Institute Creat Technology, CA 90094 USA.
    Barreto, Joseph
    USC Institute Creat Technology, CA 90094 USA.
    Alexander, Oleg
    USC Institute Creat Technology, CA 90094 USA.
    Bolas, Mark
    USC Institute Creat Technology, CA 90094 USA.
    Debevec, Paul
    USC Institute Creat Technology, CA 90094 USA.
    Unger, Jonas
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
    Time-Offset Conversations on a Life-Sized Automultiscopic Projector Array2016In: PROCEEDINGS OF 29TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, (CVPRW 2016), IEEE , 2016, p. 927-935Conference paper (Refereed)
    Abstract [en]

    We present a system for creating and displaying interactive life-sized 3D digital humans based on pre-recorded interviews. We use 30 cameras and an extensive list of questions to record a large set of video responses. Users access videos through a natural conversation interface that mimics face-to-face interaction. Recordings of answers, listening and idle behaviors are linked together to create a persistent visual image of the person throughout the interaction. The interview subjects are rendered using flowed light fields and shown life-size on a special rear-projection screen with an array of 216 video projectors. The display allows multiple users to see different 3D perspectives of the subject in proper relation to their viewpoints, without the need for stereo glasses. The display is effective for interactive conversations since it provides 3D cues such as eye gaze and spatial hand gestures.

  • 180.
    Jonsson, Christian
    Linköping University, Department of Science and Technology.
    Detection of annual rings in wood2008Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This report describes an annual line detection algorithm for the WoodEye quality control system. The goal with the algorithm is to find the positions of annual lines on the four surfaces of a board. The purpose is to use this result to find the inner annual ring structure of the board. The work was done using image processing techniques to analyze images collected with WoodEye. The report gives the reader an insight in the requirements of quality control systems in the woodworking industry and the benefits of automated quality control versus manual inspection. The appearance and formation of annual lines are explained on a detailed level to provide insight on how the problem should be approached. A comparison between annual rings and fingerprints are made to see if ideas from this area of pattern recognition can be adapted to annual line detection. This comparison together with a study of existing methods led to the implementation of a fingerprint enhancement method. This method became a central part of the annual line detection algorithm. The annual line detection algorithm consists of two main steps; enhancing the edges of the annual rings, and tracking along the edges to form lines. Different solutions for components of the algorithm were tested to compare performance. The final algorithm was tested with different input images to find if the annual line detection algorithm works best with images from a grayscale or an RGB camera.

  • 181.
    Jonsson, Erik
    Linköping University, Department of Electrical Engineering, Computer Vision . Linköping University, The Institute of Technology.
    Channel-Coded Feature Maps for Computer Vision and Machine Learning2008Doctoral thesis, monograph (Other academic)
    Abstract [en]

    This thesis is about channel-coded feature maps applied in view-based object recognition, tracking, and machine learning. A channel-coded feature map is a soft histogram of joint spatial pixel positions and image feature values. Typical useful features include local orientation and color. Using these features, each channel measures the co-occurrence of a certain orientation and color at a certain position in an image or image patch. Channel-coded feature maps can be seen as a generalization of the SIFT descriptor with the options of including more features and replacing the linear interpolation between bins by a more general basis function.

    The general idea of channel coding originates from a model of how information might be represented in the human brain. For example, different neurons tend to be sensitive to different orientations of local structures in the visual input. The sensitivity profiles tend to be smooth such that one neuron is maximally activated by a certain orientation, with a gradually decaying activity as the input is rotated.

    This thesis extends previous work on using channel-coding ideas within computer vision and machine learning. By differentiating the channel-coded feature maps with respect to transformations of the underlying image, a method for image registration and tracking is constructed. By using piecewise polynomial basis functions, the channel coding can be computed more efficiently, and a general encoding method for N-dimensional feature spaces is presented.

    Furthermore, I argue for using channel-coded feature maps in view-based pose estimation, where a continuous pose parameter is estimated from a query image given a number of training views with known pose. The optimization of position, rotation and scale of the object in the image plane is then included in the optimization problem, leading to a simultaneous tracking and pose estimation algorithm. Apart from objects and poses, the thesis examines the use of channel coding in connection with Bayesian networks. The goal here is to avoid the hard discretizations usually required when Markov random fields are used on intrinsically continuous signals like depth for stereo vision or color values in image restoration.

    Channel coding has previously been used to design machine learning algorithms that are robust to outliers, ambiguities, and discontinuities in the training data. This is obtained by finding a linear mapping between channel-coded input and output values. This thesis extends this method with an incremental version and identifies and analyzes a key feature of the method -- that it is able to handle a learning situation where the correspondence structure between the input and output space is not completely known. In contrast to a traditional supervised learning setting, the training examples are groups of unordered input-output points, where the correspondence structure within each group is unknown. This behavior is studied theoretically and the effect of outliers and convergence properties are analyzed.

    All presented methods have been evaluated experimentally. The work has been conducted within the cognitive systems research project COSPAL funded by EC FP6, and much of the contents has been put to use in the final COSPAL demonstrator system.

  • 182.
    Jonsson, Peter
    et al.
    Division of Solid State Physics, Lund University, SE-22100 Lund, Sweden.
    Jonsson, Magnus P.
    Division of Solid State Physics, Lund University, SE-22100 Lund, Sweden.
    Tegenfeldt, Jonas O.
    Division of Solid State Physics, Lund University, SE-22100 Lund, Sweden.
    Hook, Fredrik
    Division of Solid State Physics, Lund University, SE-22100 Lund, Sweden.
    A Method Improving the Accuracy of Fluorescence Recovery after Photobleaching Analysis2008In: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 95, no 11, p. 5334-5348Article in journal (Refereed)
    Abstract [en]

    Fluorescence recovery after photobleaching has been an established technique of quantifying the mobility of molecular species in cells and cell membranes for more than 30 years. However, under nonideal experimental conditions, the current methods of analysis still suffer from occasional problems; for example, when the signal/noise ratio is low, when there are temporal fluctuations in the illumination, or when there is bleaching during the recovery process. We here present a method of analysis that overcomes these problems, yielding accurate results even under nonideal experimental conditions. The method is based on circular averaging of each image, followed by spatial frequency analysis of the averaged radial data, and requires no prior knowledge of the shape of the bleached area. The method was validated using both simulated and experimental fluorescence recovery after photobleaching data, illustrating that the diffusion coefficient of a single diffusing component can be determined to within similar to 1%, even for small signal levels (100 photon counts), and that at typical signal levels (5000 photon counts) a system with two diffusion coefficients can be analyzed with less than 10% error.

  • 183.
    Julià, Carme
    et al.
    Rovira i Virgili University, Spain.
    Moreno, Rodrigo
    Rovira i Virgili University, Spain.
    Puig, Domenec
    Rovira i Virgili University, Spain.
    Garcia, Miguel Angel
    Autonomous University of Madrid, Spain.
    Shape-based image segmentation through photometric stereo2011In: Computer Vision and Image Understanding, ISSN 1077-3142, E-ISSN 1090-235X, Vol. 115, no 1, p. 91-104Article in journal (Refereed)
    Abstract [en]

    This paper describes a new algorithm for segmenting 2D images by taking into account 3D shape information. The proposed approach consists of two stages. In the first stage, the 3D surface normals of the objects present in the scene are estimated through robust photometric stereo. Then, the image is segmented by grouping its pixels according to their estimated normals through graph-based clustering. One of the advantages of the proposed approach is that, although the segmentation is based on the 3D shape of the objects, the photometric stereo stage used to estimate the 3D normals only requires a set of 2D images. This paper provides an extensive validation of the proposed approach by comparing it with several image segmentation algorithms. Particularly, it is compared with both appearance-based image segmentation algorithms and shape-based ones. Experimental results confirm that the latter are more suitable when the objective is to segment the objects or surfaces present in the scene. Moreover, results show that the proposed approach yields the best image segmentation in most of the cases.

  • 184.
    Järemo-Lawin, Felix
    et al.
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Danelljan, Martin
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Tosteberg, Patrik
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Bhat, Goutam
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Khan, Fahad Shahbaz
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Felsberg, Michael
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Deep Projective 3D Semantic Segmentation2017In: Computer Analysis of Images and Patterns: 17th International Conference, CAIP 2017, Ystad, Sweden, August 22-24, 2017, Proceedings, Part I / [ed] Michael Felsberg, Anders Heyden and Norbert Krüger, Springer, 2017, p. 95-107Conference paper (Refereed)
    Abstract [en]

    Semantic segmentation of 3D point clouds is a challenging problem with numerous real-world applications. While deep learning has revolutionized the field of image semantic segmentation, its impact on point cloud data has been limited so far. Recent attempts, based on 3D deep learning approaches (3D-CNNs), have achieved below-expected results. Such methods require voxelizations of the underlying point cloud data, leading to decreased spatial resolution and increased memory consumption. Additionally, 3D-CNNs greatly suffer from the limited availability of annotated datasets.

  • 185.
    Kargén, Rolf
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Utveckling av ett active vision system för demonstration av EDSDK++ i tillämpningar inom datorseende2014Independent thesis Basic level (degree of Bachelor), 10,5 credits / 16 HE creditsStudent thesis
    Abstract [en]

    Computer vision is a rapidly growing, interdisciplinary field whose applications are taking an increasingly prominent role in today's society. With an increased interest in computer vision there is also an increasing need to be able to control cameras connected to computer vision systems.

    At the division of computer vision, at Linköping University, the framework EDSDK++ has been developed to remotely control digital cameras made by Canon Inc. The framework is very comprehensive and contains a large amount of features and configuration options. The system is therefore largely still relatively untested. This thesis aims to develop a demonstrator to EDSDK++ in the form of a simple active vision system, which utilizes real-time face detection in order to control a camera tilt, and a camera mounted on the tilt, to follow, zoom in and focus on a face or a group of faces. A requirement was that the OpenCV library would be used for face detection and EDSDK++ would be used to control the camera. Moreover, an API to control the camera tilt was to be developed.

    During development, different methods for face detection were investigated. In order to improve performance, multiple, parallel face detectors using multithreading, were used to scan an image from different angles. Both experimental and theoretical approaches were made to determine the parameters needed to control the camera and camera tilt. The project resulted in a fully functional demonstrator, which fulfilled all requirements.

  • 186.
    Kasten, Jens
    et al.
    Zuse Institute Berlin.
    Hotz, Ingrid
    Zuse Institue Berlin.
    Hege, Hans-Christian
    Zuse Institute Berlin.
    On the Elusive Concept of Lagrangian Coherent Structures2012In: Topological Methods in Data Analysis and Visualization: Theory, Algorithms, and Applications / [ed] Ronald Peikert, Helwig Hauser, Hamish Carr, Raphael Fuchs, Springer, 2012, p. 207-220Chapter in book (Refereed)
    Abstract [en]

    Many of the recently developed methods for analysis and visualization of time-dependent flows are related to concepts, which can be subsumed under the term Lagrangian coherent structures (LCS). Thereby, no universal definition of LCS exists and different interpretations are used. Mostly, LCS are considered to be features linked to pathlines leading to the ideal conception of features building material lines. Such time-dependent features are extracted by averaging local properties of particles along their trajectories, e.g., separation, acceleration or unsteadiness. A popular realization of LCS is the finite-time Lyapunov exponent (FTLE) with its different implementations. The goal of this paper is to stimulate a discussion on the generality of the underlying assumptions and concepts. Using a few well-known datasets, the interpretation and usability of Lagrangian analysis methods are discussed.

  • 187.
    Kasten, Jens
    et al.
    Zuse Institute Berlin (ZIB), Berlin, Germany.
    Hotz, Ingrid
    Zuse Institute Berlin (ZIB), Berlin, Germany.
    Noack, Bernd
    Berlin Institute of Technology MB1, Berlin, Germany .
    Hege, Hans-Christian
    Berlin Institute of Technology MB1, Berlin, Germany .
    On the Extraction of Long-living Features in Unsteady Fluid Flows2011In: Topological Methods in Data Analysis and Visualization: Theory, Algorithms, and Applications / [ed] Valerio Pascucci, Xavier Tricoche, Hans Hagen, Julien Tierny, Springer, 2011, p. 115-126Chapter in book (Refereed)
    Abstract [en]

    This paper proposes aGalilean invariant generalization of critical points ofvector field topology for 2D time-dependent flows. The approach is based upon a Lagrangian consideration of fluid particle motion. It extracts long-living features, likesaddles and centers, and filters out short-living local structures. This is well suited for analysis ofturbulent flow, where standard snapshot topology yields an unmanageable large number of topological structures that are barely related to the few main long-living features employed in conceptual fluid mechanics models. Results are shown for periodic and chaoticvortex motion.

  • 188.
    Kasten, Jens
    et al.
    Zuse Institute Berlin, Germany.
    Hotz, Ingrid
    Zuse Institute Berlin, Germany.
    Noack, Bernd R.
    Zuse Institute Berlin, Germany.
    Hege, Hans-Christian
    Zuse Institute Berlin, Germany.
    Vortex merge graphs in two-dimensional unsteady flow fields2012Conference paper (Refereed)
    Abstract [en]

    Among the various existing vortex definitions, there is one class that relies on extremal structures of derived scalar fields. These are, e.g., vorticity,λ<sub>2</sub>, or the acceleration magnitude. This paper proposes a method to identify and track extremal-based vortex structures in 2D time-dependent flows. It is based on combinatorial scalar field topology. In contrast to previous methods, merge events are explicitly handled and represented in the resulting graph. An abstract representation of this vortex merge graph serves as basis for the comparison of the different scalar identifiers. The method is applied to numerically simulated flows of a mixing layer and a planar jet.

  • 189.
    Kasten, Jens
    et al.
    Zuse Institute Berlin, Germany.
    Reininghaus, Jan
    Zuse Institute Berlin, Germany.
    Hotz, Ingrid
    Zuse Institute Berlin, Germany.
    Hege, Hans-Christian
    Zuse Institute Berlin, Germany.
    Two-dimensional Time-dependent Vortex Regions based on the Acceleration Magnitude2011In: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, Vol. 17, no 12, p. 2080-2087Article in journal (Refereed)
    Abstract [en]

    Acceleration is a fundamental quantity of flow fields that captures Galilean invariant properties of particle motion. Considering the magnitude of this field, minima represent characteristic structures of the flow that can be classified as saddle- or vortex-like. We made the interesting observation that vortex-like minima are enclosed by particularly pronounced ridges. This makes it possible to define boundaries of vortex regions in a parameter-free way. Utilizing scalar field topology, a robust algorithm can be designed to extract such boundaries. They can be arbitrarily shaped. An efficient tracking algorithm allows us to display the temporal evolution of vortices. Various vortex models are used to evaluate the method. We apply our method to two-dimensional model systems from computational fluid dynamics and compare the results to those arising from existing definitions.

  • 190.
    Kasten, Jens
    et al.
    IVU Traff Technology AG, Germany; Zuse Institute Berlin, Germany.
    Reininghaus, Jan
    IST Austria, Austria.
    Hotz, Ingrid
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
    Hege, Hans-Christian
    Zuse Institute Berlin, Germany.
    Noack, Bernd R.
    LIMSI CNRS, France; Technical University of Carolo Wilhelmina Braunschweig, Germany.
    Daviller, Guillaume
    CNRS, France.
    Morzynski, Marek
    Poznan University of Tech, Poland.
    Acceleration feature points of unsteady shear flows2016In: ARCHIVES OF MECHANICS, ISSN 0373-2029, Vol. 68, no 1, p. 55-80Article in journal (Refereed)
    Abstract [en]

    A FRAMEWORK FOR EXTRACTING FEATURES IN 2D TRANSIENT FLOWS, based on the acceleration field to ensure Galilean invariance is proposed in this paper. The minima of the acceleration magnitude (a superset of acceleration zeros) are extracted and discriminated into vortices and saddle points, based on the spectral properties of the velocity Jacobian. The extraction of topological features is performed with purely combinatorial algorithms from discrete computational topology. The feature points are prioritized with persistence, as a physically meaningful importance mea sure. These feature points are tracked in time with a robust algorithm for tracking features. Thus, a space-time hierarchy of the minima is built and vortex merging events are detected. We apply the acceleration feature extraction strategy to three two-dimensional shear flows: (1) an incompressible periodic cylinder wake, (2) an incompressible planar mixing layer and (3) a weakly compressible planar jet. The vortex-like acceleration feature points are shown to be well aligned with acceleration zeros, maxima of the vorticity magnitude, minima of the pressure field and minima of lambda(2). Copyright (C) 2016 by IPPT PAN

  • 191.
    Kernell, Björn
    Linköping University, Department of Electrical Engineering, Computer Vision.
    Improving Photogrammetry using Semantic Segmentation2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    3D reconstruction is the process of constructing a three-dimensional model from images. It contains multiple steps where each step can induce errors. When doing 3D reconstruction of outdoor scenes, there are some types of scene content that regularly cause problems and affect the resulting 3D model. Two of these are water, due to its fluctuating nature, and sky because of it containing no useful (3D) data. These areas cause different problems throughout the process and do generally not benefit it in any way. Therefore, masking them early in the reconstruction chain could be a useful step in an outdoor scene reconstruction pipeline. Manual masking of images is a time-consuming and boring task and it gets very tedious for big data sets which are often used in large scale 3D reconstructions. This master thesis explores if this can be done automatically using Convolutional Neural Networks for semantic segmentation, and to what degree the masking would benefit a 3D reconstruction pipeline.

  • 192.
    Khan, Fahad Shahbaz
    et al.
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Beigpour, Shida
    Norwegian Colour and Visual Computing Laboratory, Gjovik University College, Gjøvik, Norway.
    van de Weijer, Joost
    Computer Vision Center, CS Dept. Universitat Autonoma de Barcelona, Spain.
    Felsberg, Michael
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Painting-91: a large scale database for computational painting categorization2014In: Machine Vision and Applications, ISSN 0932-8092, E-ISSN 1432-1769, Vol. 25, no 6, p. 1385-1397Article in journal (Refereed)
    Abstract [en]

    Computer analysis of visual art, especially paintings, is an interesting cross-disciplinary research domain. Most of the research in the analysis of paintings involve medium to small range datasets with own specific settings. Interestingly, significant progress has been made in the field of object and scene recognition lately. A key factor in this success is the introduction and availability of benchmark datasets for evaluation. Surprisingly, such a benchmark setup is still missing in the area of computational painting categorization. In this work, we propose a novel large scale dataset of digital paintings. The dataset consists of paintings from 91 different painters. We further show three applications of our dataset namely: artist categorization, style classification and saliency detection. We investigate how local and global features popular in image classification perform for the tasks of artist and style categorization. For both categorization tasks, our experimental results suggest that combining multiple features significantly improves the final performance. We show that state-of-the-art computer vision methods can correctly classify 50 % of unseen paintings to its painter in a large dataset and correctly attribute its artistic style in over 60 % of the cases. Additionally, we explore the task of saliency detection on paintings and show experimental findings using state-of-the-art saliency estimation algorithms.

  • 193.
    Khan, Fahad Shahbaz
    et al.
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Muhammad Anwer, Rao
    Department of Information and Computer Science, Aalto University School of Science, Finland.
    van de Weijer, Joost
    Computer Vision Center, CS Dept. Universitat Autonoma de Barcelona, Spain.
    Felsberg, Michael
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, The Institute of Technology.
    Laaksonen, Jorma
    Department of Information and Computer Science, Aalto University School of Science, Finland.
    Compact color–texture description for texture classification2015In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 51, p. 16-22Article in journal (Refereed)
    Abstract [en]

    Describing textures is a challenging problem in computer vision and pattern recognition. The classification problem involves assigning a category label to the texture class it belongs to. Several factors such as variations in scale, illumination and viewpoint make the problem of texture description extremely challenging. A variety of histogram based texture representations exists in literature. However, combining multiple texture descriptors and assessing their complementarity is still an open research problem. In this paper, we first show that combining multiple local texture descriptors significantly improves the recognition performance compared to using a single best method alone. This gain in performance is achieved at the cost of high-dimensional final image representation. To counter this problem, we propose to use an information-theoretic compression technique to obtain a compact texture description without any significant loss in accuracy. In addition, we perform a comprehensive evaluation of pure color descriptors, popular in object recognition, for the problem of texture classification. Experiments are performed on four challenging texture datasets namely, KTH-TIPS-2a, KTH-TIPS-2b, FMD and Texture-10. The experiments clearly demonstrate that our proposed compact multi-texture approach outperforms the single best texture method alone. In all cases, discriminative color names outperforms other color features for texture classification. Finally, we show that combining discriminative color names with compact texture representation outperforms state-of-the-art methods by 7.8%,4.3%7.8%,4.3% and 5.0%5.0% on KTH-TIPS-2a, KTH-TIPS-2b and Texture-10 datasets respectively.

  • 194.
    Khan, Fahad
    et al.
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    van de Weijer, Joost
    University of Autonoma Barcelona, Spain.
    Muhammad Anwer, Rao
    Aalto University, Finland.
    Bagdanov, Andrew D.
    University of Florence, Italy.
    Felsberg, Michael
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Laaksonen, Jorma
    Aalto University, Finland.
    Scale coding bag of deep features for human attribute and action recognition2018In: Machine Vision and Applications, ISSN 0932-8092, E-ISSN 1432-1769, Vol. 29, no 1, p. 55-71Article in journal (Refereed)
    Abstract [en]

    Most approaches to human attribute and action recognition in still images are based on image representation in which multi-scale local features are pooled across scale into a single, scale-invariant encoding. Both in bag-of-words and the recently popular representations based on convolutional neural networks, local features are computed at multiple scales. However, these multi-scale convolutional features are pooled into a single scale-invariant representation. We argue that entirely scale-invariant image representations are sub-optimal and investigate approaches to scale coding within a bag of deep features framework. Our approach encodes multi-scale information explicitly during the image encoding stage. We propose two strategies to encode multi-scale information explicitly in the final image representation. We validate our two scale coding techniques on five datasets: Willow, PASCAL VOC 2010, PASCAL VOC 2012, Stanford-40 and Human Attributes (HAT-27). On all datasets, the proposed scale coding approaches outperform both the scale-invariant method and the standard deep features of the same network. Further, combining our scale coding approaches with standard deep features leads to consistent improvement over the state of the art.

  • 195.
    Kleiner, Alexander
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Farinelli, A.
    University of Verona, Italy.
    Ramchurn, S.
    University of Southampton, UK.
    Shi, B.
    Wuhan University of Tec., China.
    Maffioletti, F.
    University of Verona, Italy.
    Reffato, R.
    University of Verona, Italy.
    RMASBench: Benchmarking Dynamic Multi-Agent Coordination in Urban Search and Rescue2013In: Proc. of the 12th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2013), The International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS) , 2013, p. 1195-1196Conference paper (Refereed)
    Abstract [en]

    We propose RMASBench, a new benchmarking tool based on the RoboCup Rescue Agent simulation system, to easily compare coordination approaches in a dynamic rescue scenario. In particular, we offer simple interfaces to plug-in coordination algorithms without the need for implementing and tuning low-level agents behaviors. Moreover, we add to the realism of the simulation by providing a large scale crowd simulator, which exploits GPUs parallel architecture, to simulate the behavior of thousands of agents in real time. Finally, we focus on a specific coordination problem where fire fighters must combat fires and prevent them from spreading across the city. We formalize this problem as a Distributed Constraint Optimization Problem and we compare two state-of-the art solution techniques: DSA and MaxSum. We perform an extensive empirical evaluation of such techniques considering several standard measures for performance (e.g. damages to buildings) and coordination overhead (e.g., message exchanged and non concurrent constraint checks). Our results provide interesting insights on limitations and benefits of DSA and MaxSum in our rescue scenario and demonstrate that RMASBench offers powerful tools to compare coordination algorithms in a dynamic environment.

  • 196.
    Kleiner, Alexander
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Kolling, Andreas
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Guaranteed Search With Large Teams of Unmanned Aerial Vehicles2013In: Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), IEEE conference proceedings, 2013, p. 2977-2983Conference paper (Refereed)
    Abstract [en]

    We consider the problem of detecting moving and evading targets by a team of coordinated unmanned aerial vehicles (UAVs) in large and complex 2D and 2.5D environments. Our approach is based on the coordination of 2D sweep lines that move through the environment to clear it from all contamination, representing the possibility of a target being located in an area, and thereby detecting all targets. The trajectories of the UAVs are implicitly given by the motion of these sweep lines and their costs are determined by the number of UAVs needed. A novel algorithm that computes low cost coordination strategies of the UAV sweep lines in simply connected polygonal environments is presented. The resulting strategies are then converted to strategies clearing multiply connected and 2.5D environments. Experiments on real and artificial elevation maps with complex visibility constraints are presented and demonstrate the feasibility and scalability of the approach. The algorithms used for the experiments are made available on a public repository.

  • 197.
    Knutsson, Hans
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Westin, Carl-Fredrik
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Laboratory of Mathematics in Imaging, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA.
    Monomial Phase: A Matrix Representation of Local Phase2014In: Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data / [ed] Carl-Fredrik Westin, Anna Vilanova, Bernhard Burgeth, Springer, 2014, p. 37-73Chapter in book (Other academic)
    Abstract [en]

    Local phase is a powerful concept which has been successfully used in many image processing applications. For multidimensional signals the concept of phase is complex and there is no consensus on the precise meaning of phase. It is, however, accepted by all that a measure of phase implicitly carries a directional reference. We present a novel matrix representation of multidimensional phase that has a number of advantages. In contrast to previously suggested phase representations it is shown to be globally isometric for the simple signal class. The proposed phase estimation approach uses spherically separable monomial filter of orders 0, 1 and 2 which extends naturally to N dimensions. For 2-dimensional simple signals the representation has the topology of a Klein bottle. For 1-dimensional signals the new phase representation reduces to the original definition of amplitude and phase for analytic signals. Traditional phase estimation using quadrature filter pairs is based on the analytic signal concept and requires a pre-defined filter direction. The new monomial local phase representation removes this requirement by implicitly incorporating local orientation. We continue to define a phase matrix product which retains the structure of the phase matrix representation. The conjugate product gives a phase difference matrix in a manner similar to the complex conjugate product of complex numbers. Two motion estimation examples are given to demonstrate the advantages of this approach.

  • 198.
    Kohei, Toko
    et al.
    Chuo University, Japan.
    Chao, Jinhui
    Chuo University, Japan.
    Lenz, Reiner
    Linköping University, Department of Science and Technology, Digital Media. Linköping University, The Institute of Technology.
    On Curvature of Color Spaces and Its Implications2010In: CGIV 2010/MCS'10 5th European Conference on Colour in Graphics, Imaging, and Vision and 12th International Symposium on Multispectral Colour Science / [ed] Jussi Parkkinen, Timo Jääskeläinen, Theo Gevers, Alain Trémeau, Springfield, VA, USA: The Society for Imaging Science and Technology, 2010, p. 393-398Conference paper (Refereed)
    Abstract [en]

    In this paper we discuss the role of curvature in the context of color spaces. Curvature is a differential geometric property of color spaces that has attracted less attention than other properties like the metric or geodesics. In this paper we argue that the curvature of a color space is important since curvature properties are essential in the construction of color coordinate systems. Only color spaces with negative or zero curvature everywhere allow the construction of Munsell-like coordinates with geodesics, shortest paths between two colors, that never intersect. In differential geometry such coordinate systems are known as Riemann coordinates and they are generalizations of the well-known polar coordinates. We investigate the properties of two measurement sets of just-noticeable-difference (jnd) ellipses and color coordinate systems constructed from them. We illustrate the role of curvature by investigating Riemann normal coordinates in CIELUV and CIELAB spaces. An algorithsm is also shown to build multipatch Riemann coordinates for spaces with the positive curvature.

  • 199.
    Kolling, Andreas
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Kleiner, Alexander
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Multi-UAV Trajectory Planning for Guaranteed Search2013In: Proc. of the 12th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2013), The International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS) , 2013, p. 79-86Conference paper (Refereed)
    Abstract [en]

    We consider the problem of detecting all moving and evading targets in 2.5D environments with teams of UAVs. Targets are assumed to be fast and omniscient while UAVs are only equipped with limited range detection sensors and have no prior knowledge about the location of targets. We present an algorithm that, given an elevation map of the environment, computes synchronized trajectories for the UAVs to guarantee the detection of all targets. The approach is based on coordinating the motion of multiple UAVs on sweep lines to clear the environment from contamination, which represents the possibility of an undetected target being located in an area. The goal is to compute trajectories that minimize the number of UAVs needed to execute the guaranteed search. This is achieved by converting 2D strategies, computed for a polygonal representation of the environment, to 2.5D strategies. We present methods for this conversion and consider cost of motion and visibility constraints. Experimental results demonstrate feasibility and scalability of the approach. Experiments are carried out on real and artificial elevation maps and provide the basis for future deployments of large teams of real UAVs for guaranteed search.

  • 200.
    Koschorrek, Philipp
    et al.
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Piccini, Tommaso
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Öberg, Per
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Felsberg, Michael
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Mester, Rudolf
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology. University of Frankfurt, Germany.
    A multi-sensor traffic scene dataset with omnidirectional video2013In: 2013 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW), IEEE conference proceedings, 2013, p. 727-734Conference paper (Refereed)
    Abstract [en]

    The development of vehicles that perceive their environment, in particular those using computer vision, indispensably requires large databases of sensor recordings obtained from real cars driven in realistic traffic situations. These datasets should be time shaped for enabling synchronization of sensor data from different sources. Furthermore, full surround environment perception requires high frame rates of synchronized omnidirectional video data to prevent information loss at any speeds.

    This paper describes an experimental setup and software environment for recording such synchronized multi-sensor data streams and storing them in a new open source format. The dataset consists of sequences recorded in various environments from a car equipped with an omnidirectional multi-camera, height sensors, an IMU, a velocity sensor, and a GPS. The software environment for reading these data sets will be provided to the public, together with a collection of long multi-sensor and multi-camera data streams stored in the developed format.

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