Face Classification via Sparse Approximation
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Date
2011
Journal Title
Journal ISSN
Volume Title
Publisher
Springer-Verlag Berlin
Access Rights
info:eu-repo/semantics/closedAccess
Abstract
We address the problem of 2D face classification under adverse conditions. Faces are difficult to recognize since they are highly variable due to such factors as illumination, expression, pose, occlusion and resolution. We investigate the potential of a method where the face recognition problem is cast as a sparse approximation. The sparse approximation provides a significant amount of robustness beneficial in mitigating various adverse effects. The study is conducted experimentally using the Extended Yale Face B database and the results are compared against the Fisher classifier benchmark.
Description
COST 2101 European Workshop on Biometrics and Identity Management (BioID) -- MAR 08-10, 2011 -- Brandenburg Univ Appl Sci, Brandenburg, GERMANY
Keywords
Face Classification, Sparse Approximation, Fisher Classifier, Recognition, Robust, Representation, Illumination
Journal or Series
Biometrics and Id Management
WoS Q Value
N/A
Scopus Q Value
Q3
Volume
6583
