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Conference Papers Year : 2008

Simultaneous learning of motion and appearance

Abstract

A new learning method for motion estimation of objects with significantly varying appearance is proposed. Varying object appearance is represented by a low dimensional space of appearance parameters. The appearance mapping and motion estimation method are optimized simultaneously. Appearance parameters are estimated by unsupervised learning. The method is experimentally verified by a tracking application on sequences which exhibit strong variable illumination, non-rigid deformations and self-occlusions.
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Dates and versions

inria-00326712 , version 1 (05-10-2008)

Identifiers

  • HAL Id : inria-00326712 , version 1

Cite

Karel Zimmermann, Tomas Svoboda, Jiri Matas. Simultaneous learning of motion and appearance. The 1st International Workshop on Machine Learning for Vision-based Motion Analysis - MLVMA'08, Oct 2008, Marseille, France. ⟨inria-00326712⟩

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MLVMA08
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