Error Correction for High-Dimensional Data via Convex Programming
Wright, John N.
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Permalink
https://hdl.handle.net/2142/81151
Description
Title
Error Correction for High-Dimensional Data via Convex Programming
Author(s)
Wright, John N.
Issue Date
2009
Doctoral Committee Chair(s)
Ma, Yi
Department of Study
Electrical and Computer Engineering
Discipline
Electrical and Computer Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Electronics and Electrical
Language
eng
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.
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