E. Arnaud, E. Mémin, B. Cernushi Frias. A robust stochastic filter for point tracking in image sequences. In Asian Conference on Computer Vision (ACCV'04), Jeju Island, Korea, January 2004.
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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
@InProceedings{Arnaud04b,
Author = {Arnaud, E. and Mémin, E. and Cernushi Frias, B.},
Title = {A robust stochastic filter for point tracking in image sequences},
BookTitle = {Asian Conference on Computer Vision (ACCV'04)},
Address = {Jeju Island, Korea},
Month = {January},
Year = {2004}
}
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