SEMD based sparse gabor representation for eyeglasses-face recognition

Authors:
Caifang Song;Baocai Yin;Yanfeng Sun
Affiliations:
Beijing Key Laboratory of Multimedia and Intelligent Software, College of Computer Science and Technology, Beijing University of Technology, Beijing, China;Beijing Key Laboratory of Multimedia and Intelligent Software, College of Computer Science and Technology, Beijing University of Technology, Beijing, China;Beijing Key Laboratory of Multimedia and Intelligent Software, College of Computer Science and Technology, Beijing University of Technology, Beijing, China
Venue:
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part II
Year:
2011

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Abstract

Sparse representation for face recognition has been exploited in past years. Several sparse representation algorithms have been developed. In this paper, a novel eyeglasses-face recognition approach, SEMD Based Sparse Gabor Representation, is proposed. Firstly, for a robust representation to misalignment, a sparse Gabor representation is proposed. Secondly, spatially constrained earth mover's distance is employed instead of Euclidean distance to measure the similarity between original data and reconstructed data. The proposed algorithm for eyeglasses-face recognition has been evaluated under different eyeglasses-face databases. The experimental results reveal that the proposed approach is validity and has better recognition performance than that obtained using other traditional methods.