UM
Huber collaborative representation for robust face identification
Wang Y.-L.3; Zou C.-M.3; Tang Y.Y.2; Yang L.-N.1
2018-11-02
Source PublicationInternational Conference on Wavelet Analysis and Pattern Recognition
Volume2018-July
Pages78-81
AbstractIn this paper, we consider the problem of recognizing human faces from the facial images of front views against random corruption. To this end, we develop a Huber collaborative representation based classification (HCRC) approach and apply it to face identification. To handle gross corruption, we exploit the robust Huber estimator as the cost function. A half-quadratic optimization algorithm is devised to solve the HCRC model efficiently. The experiments on real-life data validate the efficacy of HCRC for face identification.
KeywordCollaborative representation Face recognition M-estimation
DOI10.1109/ICWAPR.2018.8521265
URLView the original
Language英語
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Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.Guangxi University
2.Universidade de Macau
3.Chengdu University
Recommended Citation
GB/T 7714
Wang Y.-L.,Zou C.-M.,Tang Y.Y.,et al. Huber collaborative representation for robust face identification[C],2018:78-81.
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