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

Kazuo Ohzeki, Ryota Aoyama, Yutaka Hirakawa

研究成果: Conference contribution

抄録

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 adopted 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 means 3.75-7.5 Hz by frequency on average. Also, the maximum interval, which is the worst case, between the two values with minimum deviation is about 0.8 seconds for the tested feature point sample.

本文言語English
ホスト出版物のタイトルProceedings of the 2015 Federated Conference on Computer Science and Information Systems, FedCSIS 2015
編集者Marcin Paprzycki, Leszek Maciaszek, Maria Ganzha, Leszek Maciaszek
出版社Institute of Electrical and Electronics Engineers Inc.
ページ869-874
ページ数6
ISBN(電子版)9788360810651
DOI
出版ステータスPublished - 2015
イベントFederated Conference on Computer Science and Information Systems, FedCSIS 2015 - Lodz, Poland
継続期間: 2015 9 132015 9 16

出版物シリーズ

名前Proceedings of the 2015 Federated Conference on Computer Science and Information Systems, FedCSIS 2015

Other

OtherFederated Conference on Computer Science and Information Systems, FedCSIS 2015
国/地域Poland
CityLodz
Period15/9/1315/9/16

ASJC Scopus subject areas

  • コンピュータ サイエンス(全般)

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