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  • Automated Face Pose Estimation Using Elastic Energy Models

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    Author(s)
    Zhao, Sanqiang
    Gao, Yongsheng
    Griffith University Author(s)
    Gao, Yongsheng
    Year published
    2006
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    Abstract
    Face pose estimation forms an important part in a face recognition system. However, fully automated and accurate pose determination still remains an unsolved problem in the research community. In this paper, we propose a novel Elastic Energy Model to automatically estimate face poses. Our method employs statistical energy contributions of a set of feature points, which can avoid over-trusting selected anchor points. It provides a robust solution to the feature localisation inaccuracy problem, which is inevitable in practical applications with cluttered backgrounds. As a general configuration, our model can be ...
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    Face pose estimation forms an important part in a face recognition system. However, fully automated and accurate pose determination still remains an unsolved problem in the research community. In this paper, we propose a novel Elastic Energy Model to automatically estimate face poses. Our method employs statistical energy contributions of a set of feature points, which can avoid over-trusting selected anchor points. It provides a robust solution to the feature localisation inaccuracy problem, which is inevitable in practical applications with cluttered backgrounds. As a general configuration, our model can be easily implemented and extended to other non-rigid objects. Its effectiveness and robustness are revealed in our experiments.
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    Conference Title
    18TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 4, PROCEEDINGS
    Volume
    4
    DOI
    https://doi.org/10.1109/ICPR.2006.291
    Copyright Statement
    © 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
    Publication URI
    http://hdl.handle.net/10072/13121
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    • Conference outputs

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