Micro-expression recognition by feature points tracking

Shuoqing Yao*, Ning He, Huiquan Zhang, Osamu Yoshie

*この研究の対応する著者

研究成果: Conference contribution

14 被引用数 (Scopus)

抄録

One of the most interesting aspects of facial expression analysis is recognizing micro-expression. In this paper, a new feature tracking and alignment approach for micro-expression based on FACS systems and Tracking Learning Detection(TLD) is presented. The basic point for detecting first frame feature point is based on Hough Forest, and in order to increase the accuracy, we extracted features by Local Binary Pattern(LBP) as initialization. Unlike many previous works, the proposed approach applies conceptual area in perspective of human cognition. And this approach aims to track the extracted features and quantifies changing trend of these points for analyzing micro-expression. To estimate our approach's rationality, we conducted experiments on the CASME and SMIC facial expression database. The results show that the proposed approach is effective and performs well in recognizing some specific micro-expressions. Furthermore, the proposed approach is more accurate than previous methods based on Temporal Interpolation Model(TIM).

本文言語English
ホスト出版物のタイトル2014 10th International Conference on Communications, COMM 2014 - Conference Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(印刷版)9781479923854
DOI
出版ステータスPublished - 2014
イベント2014 10th International Conference on Communications, COMM 2014 - Bucharest, Romania
継続期間: 2014 5月 292014 5月 31

出版物シリーズ

名前IEEE International Conference on Communications
ISSN(印刷版)1550-3607

Conference

Conference2014 10th International Conference on Communications, COMM 2014
国/地域Romania
CityBucharest
Period14/5/2914/5/31

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • 電子工学および電気工学

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