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Johansson, Björn
Publications (10 of 30) Show all publications
Viksten, F., Forssén, P.-E., Johansson, B. & Moe, A. (2010). Local Image Descriptors for Full 6 Degree-of-Freedom Object Pose Estimation and Recognition.
Open this publication in new window or tab >>Local Image Descriptors for Full 6 Degree-of-Freedom Object Pose Estimation and Recognition
2010 (English)Article in journal (Refereed) Submitted
Abstract [en]

Recent years have seen advances in the estimation of full 6 degree-of-freedom object pose from a single 2D image. These advances have often been presented as a result of, or together with, a new local image feature type. This paper examines how the pose accuracy and recognition robustness for such a system varies with choice of feature type. This is done by evaluating a full 6 degree-of-freedom pose estimation system for 17 different combinations of local descriptors and detectors. The evaluation is done on data sets with photos of challenging 3D objects with simple and complex backgrounds and varying illumination conditions. We examine the performance of the system under varying levels of object occlusion and we find that many features allow considerable object occlusion. From the experiments we can conclude that duplet features, that use pairs of interest points, improve pose estimation accuracy, compared to single point features. Interestingly, we can also show that many features previously used for recognition and wide-baseline stereo are unsuitable for pose estimation, one notable example are the affine covariant features that have been proven quite successful in other applications. The data sets and their ground truths are available on the web to allow future comparison with novel algorithms.

Keyword
bin picking, pose estimation, local features
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:liu:diva-57330 (URN)
Note
This is an extension of http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-44894Available from: 2010-06-16 Created: 2010-06-16 Last updated: 2018-01-12
Johansson, B., Wiklund, J., Forssén, P.-E. & Granlund, G. (2009). Combining shadow detection and simulation for estimation of vehicle size and position. PATTERN RECOGNITION LETTERS, 30(8), 751-759
Open this publication in new window or tab >>Combining shadow detection and simulation for estimation of vehicle size and position
2009 (English)In: PATTERN RECOGNITION LETTERS, ISSN 0167-8655, Vol. 30, no 8, p. 751-759Article in journal (Refereed) Published
Abstract [en]

This paper presents a method that combines shadow detection and a 3D box model including shadow simulation, for estimation of size and position of vehicles. We define a similarity measure between a simulated image of a 3D box, including the box shadow, and a captured image that is classified into background/foreground/shadow. The similarity Measure is used in all optimization procedure to find the optimal box state. It is shown in a number of experiments and examples how the combination shadow detection/simulation improves the estimation compared to just using detection or simulation, especially when the shadow detection or the simulation is inaccurate. We also describe a tracking system that utilizes the estimated 3D boxes, including highlight detection, spatial window instead of a time based window for predicting heading, and refined box size estimates by weighting accumulated estimates depending oil view. Finally, we show example results.

Keyword
Vehicle tracking, 3D box model, Object size estimation, Shadow detection, Shadow simulation
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-19420 (URN)10.1016/j.patrec.2009.03.005 (DOI)
Note
Original Publication: Björn Johansson, Johan Wiklund, Per-Erik Forssén and Gösta Granlund, Combining shadow detection and simulation for estimation of vehicle size and position, 2009, PATTERN RECOGNITION LETTERS, (30), 8, 751-759. http://dx.doi.org/10.1016/j.patrec.2009.03.005 Copyright: Elsevier Science B.V., Amsterdam. http://www.elsevier.com/ Available from: 2009-06-29 Created: 2009-06-22 Last updated: 2015-12-10Bibliographically approved
Viksten, F., Forssén, P.-E., Johansson, B. & Moe, A. (2009). Comparison of Local Image Descriptors for Full 6 Degree-of-Freedom Pose Estimation. In: IEEE ICRA, 2009: 1050-4729. Paper presented at Robotics and Automation, 2009. ICRA '09. IEEE International Conference on (pp. 2779-2786). Kobe: IEEE Robotics and Automation Society
Open this publication in new window or tab >>Comparison of Local Image Descriptors for Full 6 Degree-of-Freedom Pose Estimation
2009 (English)In: IEEE ICRA, 2009: 1050-4729, Kobe: IEEE Robotics and Automation Society , 2009, p. 2779-2786Conference paper, Published paper (Refereed)
Abstract [en]

Recent years have seen advances in the estimation of full 6 degree-of-freedom object pose from a single 2D image. These advances have often been presented as a result of, or together with, a new local image descriptor. This paper examines how the performance for such a system varies with choice of local descriptor. This is done by comparing the performance of a full 6 degree-of-freedom pose estimation system for fourteen types of local descriptors. The evaluation is done on a database with photos of complex objects with simple and complex backgrounds and varying lighting conditions. From the experiments we can conclude that duplet features, that use pairs of interest points, improve pose estimation accuracy, and that affine covariant features do not work well in current pose estimation frameworks. The data sets and their ground truth is available on the web to allow future comparison with novel algorithms.

Place, publisher, year, edition, pages
Kobe: IEEE Robotics and Automation Society, 2009
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-44894 (URN)10.1109/ROBOT.2009.5152360 (DOI)000276080400185 ()78158 (Local ID)9781424427888 (ISBN)78158 (Archive number)78158 (OAI)
Conference
Robotics and Automation, 2009. ICRA '09. IEEE International Conference on
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2015-12-10
Källhammer, J.-E., Eriksson, D., Granlund, G., Felsberg, M., Moe, A., Johansson, B., . . . Forssén, P.-E. (2007). Near Zone Pedestrian Detection using a Low-Resolution FIR Sensor. In: Intelligent Vehicles Symposium, 2007 IEEE: . Istanbul, Turkey: IEEE
Open this publication in new window or tab >>Near Zone Pedestrian Detection using a Low-Resolution FIR Sensor
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2007 (English)In: Intelligent Vehicles Symposium, 2007 IEEE, Istanbul, Turkey: IEEE , 2007, , p. 339-345Conference paper, Published paper (Refereed)
Abstract [en]

This paper explores the possibility to use a single low-resolution FIR camera for detection of pedestrians in the near zone in front of a vehicle. A low resolution sensor reduces the cost of the system, as well as the amount of data that needs to be processed in each frame.

We present a system that makes use of hot-spots and image positions of a near constant bearing to detect potential pedestrians. These detections provide seeds for an energy minimization algorithm that fits a pedestrian model to the detection. Since false alarms are hard to tolerate, the pedestrian model is then tracked, and the distance-to-collision (DTC) is measured by integrating size change measurements at sub-pixel accuracy, and the car velocity. The system should only engage braking for detections on a collision course, with a reliably measured DTC.

Preliminary experiments on a number of recorded near collision sequences indicate that our method may be useful for ranges up to about 10m using an 80x60 sensor, and somewhat more using a 160x120 sensor. We also analyze the robustness of the evaluated algorithm with respect to dead pixels, a potential problem for low-resolution sensors.

Place, publisher, year, edition, pages
Istanbul, Turkey: IEEE, 2007. p. 339-345
Series
Intelligent Vehicles Symposium, ISSN 1931-0587
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-39510 (URN)10.1109/IVS.2007.4290137 (DOI)49068 (Local ID)1-4244-1067-3 (ISBN)49068 (Archive number)49068 (OAI)
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2016-05-04
Hedborg, J. & Johansson, B. (2007). Real time camera ego-motion compensation and lens undistortion on GPU.
Open this publication in new window or tab >>Real time camera ego-motion compensation and lens undistortion on GPU
2007 (English)Manuscript (preprint) (Other academic)
Abstract [en]

This paper describes a GPU implementation for simultaneous camera ego-motion compensation and lens undistortion. The main idea is to transform the image under an ego-motion constraint so that trackedpoints in the image, that are assumed to come from the ego-motion, maps as close as possible to their averageposition in time. The lens undistortion is computed si-multaneously. We compare the performance with and without compensation using two measures; mean timedifference and mean statistical background subtraction.

Publisher
p. 8
Keyword
GPU, camera ego-motion compensation, lens undistortion
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-58547 (URN)
Available from: 2010-08-18 Created: 2010-08-13 Last updated: 2011-01-25Bibliographically approved
Forssén, P.-E., Johansson, B. & Granlund, G. (2006). Channel Associative Networks for Multiple Valued Mappings. In: 2nd International Cognitive Vision Workshop (pp. 4-11).
Open this publication in new window or tab >>Channel Associative Networks for Multiple Valued Mappings
2006 (English)In: 2nd International Cognitive Vision Workshop, 2006, p. 4-11Conference paper, Published paper (Other academic)
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-36318 (URN)30975 (Local ID)30975 (Archive number)30975 (OAI)
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2015-12-10
Johansson, B., Wiklund, J. & Granlund, G. (2006). Goals and status within the IVSS project. In: Seminar on "Cognitive vision in traffic analyses": Lund, Sweden.
Open this publication in new window or tab >>Goals and status within the IVSS project
2006 (English)In: Seminar on "Cognitive vision in traffic analyses": Lund, Sweden, 2006Conference paper, Published paper (Refereed)
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-21662 (URN)
Available from: 2009-10-08 Created: 2009-10-05 Last updated: 2009-10-08
Johansson, B., Elfving, T., Kozlov, V., Censor, Y., Forssén, P.-E. & Granlund, G. (2006). The application of an oblique-projected Landweber method to a model of supervised learning. Mathematical and computer modelling, 43(7-8), 892-909
Open this publication in new window or tab >>The application of an oblique-projected Landweber method to a model of supervised learning
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2006 (English)In: Mathematical and computer modelling, ISSN 0895-7177, E-ISSN 1872-9479, Vol. 43, no 7-8, p. 892-909Article in journal (Refereed) Published
Abstract [en]

This paper brings together a novel information representation model for use in signal processing and computer vision problems, with a particular algorithmic development of the Landweber iterative algorithm. The information representation model allows a representation of multiple values for a variable as well as an expression for confidence. Both properties are important for effective computation using multi-level models, where a choice between models will be implementable as part of the optimization process. It is shown that in this way the algorithm can deal with a class of high-dimensional, sparse, and constrained least-squares problems, which arise in various computer vision learning tasks, such as object recognition and object pose estimation. While the algorithm has been applied to the solution of such problems, it has so far been used heuristically. In this paper we describe the properties and some of the peculiarities of the channel representation and optimization, and put them on firm mathematical ground. We consider the optimization a convexly constrained weighted least-squares problem and propose for its solution a projected Landweber method which employs oblique projections onto the closed convex constraint set. We formulate the problem, present the algorithm and work out its convergence properties, including a rate-of-convergence result. The results are put in perspective with currently available projected Landweber methods. An application to supervised learning is described, and the method is evaluated in an experiment involving function approximation, as well as application to transient signals. © 2006 Elsevier Ltd. All rights reserved.

Keyword
Channel representation, Nonnegative constraint, Preconditioner, Projected Landweber, Supervised learning
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-50254 (URN)10.1016/j.mcm.2005.12.010 (DOI)
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2017-12-12
Forssén, P.-E., Johansson, B. & Granlund, G. (2005). Learning under Perceptual Aliasing.
Open this publication in new window or tab >>Learning under Perceptual Aliasing
2005 (English)Report (Other academic)
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-36327 (URN)LiTH-ISY-R-2705 (ISRN)30985 (Local ID)30985 (Archive number)30985 (OAI)
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2015-12-10
Johansson, B. & Moe, A. (2005). Object Recognition in 3D Laser Radar Data using Plane triplets. Linköping: Linköping University Electronic Press
Open this publication in new window or tab >>Object Recognition in 3D Laser Radar Data using Plane triplets
2005 (English)Report (Other academic)
Abstract [en]

This report describes a method to detect and recognize objects from 3D laser radar data. The method is based on local descriptors computed from triplets of planes that are estimated from the data set. Each descriptor that is computed on query data is compared with descriptors computed on object model data to get a hypothesis of object class and pose. An hypothesis is either verified or rejected using a similarity measure between the model data set and the query data set.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2005. p. 22
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2708
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-36325 (URN)LiTH-ISY-R-2708 (ISRN)30983 (Local ID)30983 (Archive number)30983 (OAI)
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2014-08-28Bibliographically approved
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