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A robust stochastic filter for point tracking in image sequences
Abstract : The approach we investigate for point tracking combines within a stochastic filtering framework a dynamic model relying on the optical flow constraint and measurements provided by a matching technique. Focusing on points belonging to regions described by a global dominant motion, the proposed tracking system is linear. Since we focus on the case where the system depends on the images, the tracker is built from a Conditional Linear Filter, derived through the use of a conditional linear minimum variance estimator. This conditional tracker authorizes to significantly improve results in some general situation. In particular, such an approach allows us to deal in a simple way with the tracking of points following trajectories with abrupt changes and occlusions.
Cited literature [10 references]
https://hal.inria.fr/inria-00306728
Contributor : Elise Arnaud <>
Submitted on : Tuesday, April 21, 2009 - 1:41:00 PM
Last modification on : Friday, July 10, 2020 - 4:12:02 PM
Long-term archiving on: : Saturday, November 26, 2016 - 12:34:23 AM
Contributor : Elise Arnaud <>
Submitted on : Tuesday, April 21, 2009 - 1:41:00 PM
Last modification on : Friday, July 10, 2020 - 4:12:02 PM
Long-term archiving on: : Saturday, November 26, 2016 - 12:34:23 AM
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Accv04Arnaud.pdf
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