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  • Lip Segmentation with the Presence of Beards

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    43496_1.pdf (145.6Kb)
    Author
    ang, S.
    Lau, W.
    Leung, S.
    Liew, A.
    Year published
    2004
    Metadata
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    Abstract
    Lip image analysis has attracted much interest in recent years because some important speech information is contained in the shape and movement of the lip. To extract such information from the lip images, accurate and robust lip region segmentation is of vital importance. However, most of the current lip segmentation methods fail to provide accurate results if the person has beards. In this paper, we propose a "one object, multiple background" clustering method to solve the problem. Since the non-lip region becomes inhomogeneous in the presence of beards, multiple background clusters can produce better fitting to a rather ...
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    Lip image analysis has attracted much interest in recent years because some important speech information is contained in the shape and movement of the lip. To extract such information from the lip images, accurate and robust lip region segmentation is of vital importance. However, most of the current lip segmentation methods fail to provide accurate results if the person has beards. In this paper, we propose a "one object, multiple background" clustering method to solve the problem. Since the non-lip region becomes inhomogeneous in the presence of beards, multiple background clusters can produce better fitting to a rather complex background region than one single cluster. Spatial information in terms of the physical distance towards the lip center is incorporated to enhance the differentiation between the lip and background region. Experimental results demonstrate that our algorithm provides accurate lip segmentation results for the images with beards.
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    Conference Title
    Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP'04
    DOI
    https://doi.org/10.1109/ICASSP.2004.1326598
    Copyright Statement
    © 2004 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/10072/24592
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    • Conference outputs

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