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Real-Time Visual Recognition of Objects and Scenes Using P-Channel Matching
Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.ORCID-id: 0000-0002-6096-3648
Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
2007 (Engelska)Ingår i: Proceedings 15th Scandinavian Conference on Image Analysis / [ed] Bjarne K. Ersboll and Kim S. Pedersen, Berlin, Heidelberg: Springer, 2007, Vol. 4522, s. 908-917Konferensbidrag, Publicerat paper (Refereegranskat)
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.

Ort, förlag, år, upplaga, sidor
Berlin, Heidelberg: Springer, 2007. Vol. 4522, s. 908-917
Serie
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 4522
Nyckelord [en]
Object recognition - scene registration - P-channels - real-time processing - view-based computer vision
Nationell ämneskategori
Teknik och teknologier
Identifikatorer
URN: urn:nbn:se:liu:diva-21618DOI: 10.1007/978-3-540-73040-8ISBN: 978-3-540-73039-2 (tryckt)OAI: oai:DiVA.org:liu-21618DiVA, id: diva2:241583
Konferens
15th Scandinavian Conference, SCIA 2007, June 10-24, Aalborg, Denmark
Anmärkning

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. http://dx.doi.org/10.1007/978-3-540-73040-8 Copyright: Springer

Tillgänglig från: 2009-10-05 Skapad: 2009-10-05 Senast uppdaterad: 2017-03-23Bibliografiskt granskad
Ingår i avhandling
1. Pose Estimation and Structure Analysisof Image Sequences
Öppna denna publikation i ny flik eller fönster >>Pose Estimation and Structure Analysisof Image Sequences
2009 (Engelska)Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
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.

Ort, förlag, år, upplaga, sidor
Linköping: Linköping University Electronic Press, 2009. s. 28
Serie
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1418
Nyckelord
KLT, GPU, structure from motion, stereo, pose estimation
Nationell ämneskategori
Teknik och teknologier Datorseende och robotik (autonoma system) Signalbehandling
Identifikatorer
urn:nbn:se:liu:diva-58706 (URN)LiU-TEK-LIC-2009:26 (Lokalt ID)978-91-7393-516-6 (ISBN)LiU-TEK-LIC-2009:26 (Arkivnummer)LiU-TEK-LIC-2009:26 (OAI)
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Handledare
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Tillgänglig från: 2011-01-25 Skapad: 2010-08-23 Senast uppdaterad: 2018-01-12Bibliografiskt granskad

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Felsberg, MichaelHedborg, Johan

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