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  • Face Recognition using Ensemble String Matching

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    Author(s)
    Chen, Weiping
    Gao, Yongsheng
    Griffith University Author(s)
    Gao, Yongsheng
    Chen, Weiping
    Year published
    2013
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    Abstract
    In this paper, we present a syntactic string matching approach to solve the frontal face recognition problem. String matching is a powerful partial matching technique, but is not suitable for frontal face recognition due to its requirement of globally sequential representation and the complex nature of human faces, containing discontinuous and non-sequential features. Here we build a compact syntactic Stringface representation, which is an ensemble of strings. A novel Ensemble String Matching approach that can perform non-sequential string matching between two Stringfaces is proposed. It is invariant to the sequential order ...
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    In this paper, we present a syntactic string matching approach to solve the frontal face recognition problem. String matching is a powerful partial matching technique, but is not suitable for frontal face recognition due to its requirement of globally sequential representation and the complex nature of human faces, containing discontinuous and non-sequential features. Here we build a compact syntactic Stringface representation, which is an ensemble of strings. A novel Ensemble String Matching approach that can perform non-sequential string matching between two Stringfaces is proposed. It is invariant to the sequential order of strings and the direction of each string. The embedded partial matching mechanism enables our method to automatically utilize every piece of non-occluded region, regardless of shape, in the recognition process. The encouraging results demonstrate the feasibility and effectiveness of using syntactic methods for face recognition from a single exemplar image per person, breaking the barrier that prevents string matching techniques from being utilized for addressing complex image recognition problems. The proposed method not only achieved significantly better performance in recognizing partially occluded faces, but also showed its ability to perform direct matching between sketch faces and photo faces.
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    Journal Title
    IEEE Transactions on Image Processing
    Volume
    22
    Issue
    12
    DOI
    https://doi.org/10.1109/TIP.2013.2277920
    Copyright Statement
    © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subject
    Computer vision
    Cognitive and computational psychology
    Publication URI
    http://hdl.handle.net/10072/54416
    Collection
    • Journal articles

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