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  • Eye extraction using spatial fuzzy clustering method

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    43563_1.pdf (455.3Kb)
    Author(s)
    Tse, KW
    Lau, WH
    Leung, SH
    Liew, AWC
    Griffith University Author(s)
    Liew, Alan Wee-Chung
    Year published
    2002
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    Abstract
    Facial features extraction and tracking are crucial steps for many multimedia communication applications such as automated visual interpretation, human face recognition, and development of high quality model-based coding (e.g. MPEG-4) systems. Among different facial features, eyes and lip play an important role in either recognition process or teleconferencing applications. However, automatic human facial features detection is a difficult task due to different scale, rotation and translation of the features. This paper describes a computational approach for locating the eye position from a given eye window. The proposed ...
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    Facial features extraction and tracking are crucial steps for many multimedia communication applications such as automated visual interpretation, human face recognition, and development of high quality model-based coding (e.g. MPEG-4) systems. Among different facial features, eyes and lip play an important role in either recognition process or teleconferencing applications. However, automatic human facial features detection is a difficult task due to different scale, rotation and translation of the features. This paper describes a computational approach for locating the eye position from a given eye window. The proposed algorithm extracts the eye in two stages. The iris first is extracted using a region-based energy minimization approach from the membership map generated by the spatial fuzzy clustering technique. In second two, control points are detected to locate the sclera and two parabolas are used to model the upper and lower eyelids. Satisfactory results have been achieved with the proposed method.
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    Conference Title
    2002 IEEE REGION 10 CONFERENCE ON COMPUTERS, COMMUNICATIONS, CONTROL AND POWER ENGINEERING, VOLS I-III, PROCEEDINGS
    Volume
    1
    DOI
    https://doi.org/10.1109/TENCON.2002.1181326
    Copyright Statement
    © 2002 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/10072/24520
    Collection
    • Conference outputs

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