Minimum variance method to obtain the best shot in video and its effectiveness for face recognition

Kazuo Ohzeki, Ryota Aoyama, Yutaka Hirakawa

研究成果: Article

抜粋

This paper describes a face recognition algorithm using feature points of face parts, which is classified as a feature-based method. As recognition performance depends on the combination of extracted feature points, we utilize all reliable feature points effectively. From moving video input, well-conditioned face images with a frontal direction and without facial expression are extracted. To select such well-conditioned images, an iteratively minimizing variance method is used with variable input face images. This iteration drastically brings convergence to the minimum variance of 1 for a quarter to an eighth of all data, which proves to take the frontal image in 0.27 second from video at most. The proposed system using six statistic values realizes 98.3% as an authentication rate.

元の言語English
ページ(範囲)29-44
ページ数16
ジャーナルInternational Journal of Computer Science and Applications
13
発行部数2
出版物ステータスPublished - 2016

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ASJC Scopus subject areas

  • Computer Science Applications

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