DocumentCode :
2082542
Title :
Kernel-based Template Alignment
Author :
Guskov, Igor
Author_Institution :
University of Michigan, Ann Arbor
Volume :
1
fYear :
2006
fDate :
17-22 June 2006
Firstpage :
610
Lastpage :
617
Abstract :
This paper introduces a novel kernel-based method for template tracking in video sequences. The method is derived for a general warping transformation, and its application to affine motion tracking is further explored. Our approach is based on maximization of the multi-kernel Bhattacharyya coefficient with respect to the warp parameters. We explicitly compute the gradient of the similarity functional, and use a quasi-Newton procedure for optimization. Additionally, we consider a simple extension of the method that employs an illumination model correction to allow tracking under varying lighting conditions. The resulting tracking procedure is evaluated on a number of examples including large templates tracking non-rigidly moving textured areas.
Keywords :
Image coding; Lighting; Motion estimation; Robustness; Shape; Surface texture; Surveillance; Target tracking; Video compression; Video sequences;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on
ISSN :
1063-6919
Print_ISBN :
0-7695-2597-0
Type :
conf
DOI :
10.1109/CVPR.2006.162
Filename :
1640811
Link To Document :
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