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Title:Error Correction for High-Dimensional Data via Convex Programming
Author(s):Wright, John N.
Doctoral Committee Chair(s):Ma, Yi
Department / Program:Electrical and Computer Engineering
Discipline:Electrical and Computer Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Engineering, Electronics and Electrical
Abstract:Finally, we show how these theoretical developments lead to simple, scalable, and robust algorithms for face recognition in the presence of varying illumination and occlusion. The idea is extremely simple: seek the sparsest representation of the test image as a linear combination of training images plus a sparse error term due to occlusion. In addition to achieving excellent performance on public databases, this approach sheds light on several important issues in face recognition, such as the choice of features and robustness to corruption and occlusion.
Issue Date:2009
Type:Text
Language:English
Description:199 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2009.
URI:http://hdl.handle.net/2142/81151
Other Identifier(s):(MiAaPQ)AAI3395542
Date Available in IDEALS:2015-09-25
Date Deposited:2009


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