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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Displacement Template with Divide-&-Conquer Algorithm for Significantly Improving Descriptor Based Face Recognition Approaches
verfasst von : Liang Chen, Ling Yan, Yonghuai Liu, Lixin Gao, Xiaoqin Zhang
Erschienen in: Computer Vision – ECCV 2012
Verlag: Springer Berlin Heidelberg
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This paper proposes a displacement template structure for improving descriptor based face recognition approaches. With this template structure, a face is represented by a template consisting of a set of piled blocks; each block pile consists of a few heavily overlapped blocks from the face image. An ensemble of blocks, one from each pile, is taken as a candidate image of the face. When a descriptor based approach is used, we are able to generate a displacement description template for the face by replacing each block in the template with its local description, where a concatenation of the local descriptions of the blocks, one from each pile, is taken to be a candidate description of the face. Using the description template together with a divide-and-conquer algorithm for computing the similarities between description templates, we have demonstrated the significantly improved performance of LBP, TPLBP and FPLBP templates over original LBP, TPLBP and FPLBP approaches by the experiments on benchmark face databases.