Robust Subspace Estimation Using Low-Rank Optimization: Theory and Applications

by Mubarak Shah and Omar Oreifej

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Various fundamental applications in computer vision and machine learning require finding the basis of a certain subspace. Examples of such applications include face detection, motion estimation, and activity recognition. An increasing interest has been recently placed on this area as a result of significant advances in the mathematics of matrix rank optimization. Interestingly, robust subspace estimation can be posed as a low-rank optimization problem,...

Format:Hardcover

Language:English

ISBN:3319041835

ISBN13:9783319041834

Release Date:April 2014

Publisher:Springer

Length:114 Pages

Weight:0.85 lbs.

Dimensions:0.5" x 6.0" x 9.2"

Related Subjects

Computers Computers & Technology

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Robust Subspace Estimation Using Low-Rank Optimization: Theory and Applications

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