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A 3D facial feature point localization method based on statistical shape model

  • Beihang University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Registration is a necessary step for automatic 3D face recognition systems, and feature point localization is usually used to find the correspondence in registration. Traditional localization methods are sensitive to pose changes, and can only deal with frontal or limited pose variations. In this paper we propose a new 3D facial feature point localization method that is insensitive to pose variation. Feature regions are firstly segmented out based on Shape Index features, and then selected by a statistical shape model. Point nearest to the region center is chosen as a feature point. Experimental results show that the localization accuracy is comparable to manually labeled feature points.

源语言英语
主期刊名2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
II249-II252
DOI
出版状态已出版 - 2007
活动2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 - Honolulu, HI, 美国
期限: 15 4月 200720 4月 2007

出版系列

姓名ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
2
ISSN(印刷版)1520-6149

会议

会议2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
国家/地区美国
Honolulu, HI
时期15/04/0720/04/07

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