Media-integrated biometric person recognition based on the Dempster-Shafer theory

Yoshiaki Sugie, Tetsunori Kobayashi

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    10 Citations (Scopus)

    Abstract

    The present paper describes a new integration method of speech and facial image information for person recognition problems based on the Dempster-Shafer probability theory. The Dempster-Shafer theory provides an attractive methodology by which to integrate multiple numerical evidences containing ambiguities. However, no concrete and reasonable methodology exists to enumerate the reliability of evidences. In the present paper, this problem is solved using the cumulative density function of both the correct and incorrect categories. The proposed enumerating method allows the Dempster-Shafer theory to be applied to media integration. We show that the total performance of person recognition, including rejection of unregistered users, is improved significantly using the proposed method.

    Original languageEnglish
    Title of host publicationProceedings - International Conference on Pattern Recognition
    Pages381-384
    Number of pages4
    Volume16
    Edition4
    Publication statusPublished - 2002

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    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Computer Vision and Pattern Recognition
    • Hardware and Architecture

    Cite this

    Sugie, Y., & Kobayashi, T. (2002). Media-integrated biometric person recognition based on the Dempster-Shafer theory. In Proceedings - International Conference on Pattern Recognition (4 ed., Vol. 16, pp. 381-384)