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    Biview face recognition in the shape–texture domain

    Xiao, B. and Gao, X. and Tao, D. and Li, Xuelong (2013) Biview face recognition in the shape–texture domain. Pattern Recognition 46 (7), pp. 1906-1919. ISSN 0031-3203.

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    Abstract

    Face recognition is one of the biometric identification methods with the highest potential. The existing face recognition algorithms relying on the texture information of face images are affected greatly by the variation of expression, scale and illumination. Whereas the algorithms based on the shape topology weaken the influence of illumination to some extent, but the impact of expression, scale and illumination on face recognition is still unsolved. To this end, we propose a new method for face recognition by integrating texture information with shape information, called biview face recognition algorithm. The texture models are constructed by using subspace learning methods and shape topologies are formed by building graphs for face images. The proposed biview face recognition method is compared with recognition algorithms merely based on texture or shape information. Experimental results of recognizing faces under the variation of illumination, expression and scale demonstrate that the performance of the proposed biview face recognition outperforms texture-based and shape-based algorithms.

    Metadata

    Item Type: Article
    Keyword(s) / Subject(s): face recognition, texture model, shape topology, graph edit distance, active appearance model
    School: School of Business, Economics & Informatics > Computer Science and Information Systems
    Depositing User: Sarah Hall
    Date Deposited: 06 Jun 2013 10:18
    Last Modified: 11 Oct 2016 15:27
    URI: https://eprints.bbk.ac.uk/id/eprint/7297

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