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

Yoshiaki Sugie, Tetsunori Kobayashi

研究成果: Article

10 引用 (Scopus)

抜粋

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.

元の言語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
発行部数4
出版物ステータスPublished - 2002 12 1

    フィンガープリント

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

これを引用