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

Yoshiaki Sugie*, Tetsunori Kobayashi

*この研究の対応する著者

研究成果: Article査読

10 被引用数 (Scopus)

抄録

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.

本文言語English
ページ(範囲)381-384
ページ数4
ジャーナルProceedings - International Conference on Pattern Recognition
16
4
出版ステータスPublished - 2002 12 1

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識

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