Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/12996
Title: Sparse cost-sensitive classifier with application to face recognition
Authors: Man, J
Jing, X
Zhang, D 
Lan, C
Keywords: Cost-sensitive learning
Face recognition
Sparse cost-sensitive classifier
Sparse representation
Issue Date: 2011
Source: Proceedings - International Conference on Image Processing, ICIP, 2011, p. 1773-1776 How to cite?
Abstract: Sparse representation technique has been successfully employed to solve face recognition task. Though current sparse representation based classifier proves to achieve high classification accuracy, it implicitly assumes that the losses of all misclassifications are the same. However, in many real-world applications, different misclassifications could lead to different losses. Driven by this concern, we propose in this paper a sparse cost-sensitive classifier for face recognition. Our approach uses probabilistic model of sparse representation to estimate the posterior probabilities of a testing sample, calculates all the misclassification losses via the posterior probabilities and then predicts the class label by minimizing the losses. Experimental results on the public AR and FRGC face databases validate the efficacy of the proposed approach.
Description: 2011 18th IEEE International Conference on Image Processing, ICIP 2011, Brussels, 11-14 September 2011
URI: http://hdl.handle.net/10397/12996
ISBN: 9781457713033
ISSN: 1522-4880
DOI: 10.1109/ICIP.2011.6115804
Appears in Collections:Conference Paper

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