Robust Corner Tracking for Real-Time Augmented Reality

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ConferenceIn Vision Interface 2002, May 2002., Calgary, Alberta, Canada
Subjectcorner tracking; pattern tracking; blob finding; robust; computer vision; augmented reality; poursuite de forme; recherche de « BLOB »; robustesse; vision par ordinateur; réalité augmentée
AbstractVision-based registration techniques for augmented reality systems have been the subject of intensive research recently due to their potential to accurately align virtual objects with the real world. The downfall of these vision-based approaches, however, is their high computational cost and lack of robustness. This paper describes the implementation of a fast, but accurate, vision-based corner tracker that forms the basis of a pattern-based augmented reality system. The tracker predicts corner positions by computing a homography between known corner positions on a planar pattern and potential planar regions in a video sequence. Local search windows are then placed around these predicted locations in order to find the actual subpixel corner positions. Experimental results show the robustness of the corner tracking system with respect to occlusion, scale, orientation, and lighting.
Publication date
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number45860
NPARC number9062774
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Record identifiera720ec20-3b6a-4863-b657-dd5264684380
Record created2009-05-08
Record modified2016-05-09
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