Micro-expression recognition by feature points tracking

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

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Citations (Scopus)


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).

Original languageEnglish
Title of host publication2014 10th International Conference on Communications, COMM 2014 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781479923854
Publication statusPublished - 2014
Event2014 10th International Conference on Communications, COMM 2014 - Bucharest, Romania
Duration: 2014 May 292014 May 31

Publication series

NameIEEE International Conference on Communications
ISSN (Print)1550-3607


Conference2014 10th International Conference on Communications, COMM 2014


  • Hough Forest
  • Local Binary Pattern
  • Micro-Expression
  • Temporal Interpolation Model
  • Tracking Learning Detection

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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