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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Dense linear-time correspondences for tracking
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
Stepan Obdrzalek, Center for Machine Perception, Czech Technical University Prague, Czech Republic
Michal Perd'och, Center for Machine Perception, Czech Technical University Prague, Czech Republic
Jiri Matas, Center for Machine Perception, Czech Technical University Prague, Czech Republic
A novel method is proposed for the problem of frame-to-frame correspondence search in video sequences. The method, based on hashing of low-dimensional image descriptors, establishes dense correspondences and allows large motions. All image pixels are considered for matching, the notion of interest points is reviewed. In our formulation, points of interest are those that can be reliably matched. Their saliency depends on properties of the chosen matching function and on actual image content.
Citation:
Stepan Obdrzalek, Michal Perd'och, Jiri Matas, "Dense linear-time correspondences for tracking," cvprw, pp.1-8, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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