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Real-Time Visual Recognition of Objects and Scenes Using P-Channel Matching
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
2007 (English)In: Proceedings 15th Scandinavian Conference on Image Analysis / [ed] Bjarne K. Ersboll and Kim S. Pedersen, Berlin, Heidelberg: Springer-Verlag , 2007, Vol. 4522, 908-917 p.Conference paper (Refereed)
Abstract [en]

In this paper we propose a new approach to real-time view-based object recognition and scene registration. Object recognition is an important sub-task in many applications, as e.g., robotics, retrieval, and surveillance. Scene registration is particularly useful for identifying camera views in databases or video sequences. All of these applications require a fast recognition process and the possibility to extend the database with new material, i.e., to update the recognition system online. The method that we propose is based on P-channels, a special kind of information representation which combines advantages of histograms and local linear models. Our approach is motivated by its similarity to information representation in biological systems but its main advantage is its robustness against common distortions as clutter and occlusion. The recognition algorithm extracts a number of basic, intensity invariant image features, encodes them into P-channels, and compares the query P-channels to a set of prototype P-channels in a database. The algorithm is applied in a cross-validation experiment on the COIL database, resulting in nearly ideal ROC curves. Furthermore, results from scene registration with a fish-eye camera are presented.

Place, publisher, year, edition, pages
Berlin, Heidelberg: Springer-Verlag , 2007. Vol. 4522, 908-917 p.
, Lecture Notes in Computer Science, ISSN 1611-33490 ; Volume 4522
Keyword [en]
Object recognition - scene registration - P-channels - real-time processing - view-based computer vision
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-21618DOI: 10.1007/978-3-540-73040-8ISBN: 978-3-540-73039-2OAI: diva2:241583
15th Scandinavian Conference, SCIA 2007, June 10-24, Aalborg, Denmark
Original Publication: Michael Felsberg and Johan Hedborg, Real-Time Visual Recognition of Objects and Scenes Using P-Channel Matching, 2007, Proc. 15th Scandinavian Conference on Image Analysis, 908-917. Copyright: Springer Available from: 2009-10-05 Created: 2009-10-05 Last updated: 2011-01-25
In thesis
1. Pose Estimation and Structure Analysisof Image Sequences
Open this publication in new window or tab >>Pose Estimation and Structure Analysisof Image Sequences
2009 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Autonomous navigation for ground vehicles has many challenges. Autonomous systems must be able to self-localise, avoid obstacles and determine navigable surfaces. This thesis studies several aspects of autonomous navigation with a particular emphasis on vision, motivated by it being a primary component for navigation in many high-level biological organisms.  The key problem of self-localisation or pose estimation can be solved through analysis of the changes in appearance of rigid objects observed from different view points. We therefore describe a system for structure and motion estimation for real-time navigation and obstacle avoidance. With the explicit assumption of a calibrated camera, we have studied several schemes for increasing accuracy and speed of the estimation.The basis of most structure and motion pose estimation algorithms is a good point tracker. However point tracking is computationally expensive and can occupy a large portion of the CPU resources. In thisthesis we show how a point tracker can be implemented efficiently on the graphics processor, which results in faster tracking of points and the CPU being available to carry out additional processing tasks.In addition we propose a novel view interpolation approach, that can be used effectively for pose estimation given previously seen views. In this way, a vehicle will be able to estimate its location by interpolating previously seen data.Navigation and obstacle avoidance may be carried out efficiently using structure and motion, but only whitin a limited range from the camera. In order to increase this effective range, additional information needs to be incorporated, more specifically the location of objects in the image. For this, we propose a real-time object recognition method, which uses P-channel matching, which may be used for improving navigation accuracy at distances where structure estimation is unreliable.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2009. 28 p.
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1418
KLT, GPU, structure from motion, stereo, pose estimation
National Category
Engineering and Technology Computer Vision and Robotics (Autonomous Systems) Signal Processing
urn:nbn:se:liu:diva-58706 (URN)LiU-TEK-LIC-2009:26 (Local ID)978-91-7393-516-6 (ISBN)LiU-TEK-LIC-2009:26 (Archive number)LiU-TEK-LIC-2009:26 (OAI)
Available from: 2011-01-25 Created: 2010-08-23 Last updated: 2011-01-25Bibliographically approved

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