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.
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Song, C., Yin, B., Sun, Y. (2011). SEMD Based Sparse Gabor Representation for Eyeglasses-Face Recognition. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2011. Lecture Notes in Computer Science, vol 6754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21596-4_21
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DOI: https://doi.org/10.1007/978-3-642-21596-4_21
Publisher Name: Springer, Berlin, Heidelberg
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