Facial expression recognition in video sequences

Shenchuan Tai, Hungfu Huang

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

11 Citations (Scopus)


This paper proposes asystem forthe facial expression recognition. Firstly, we perform noise reduction by a median filter of facial expression image. Then, a cross-correlation of optical flow and mathematical models from the facial points are used. To define these facial points of interest in the first frame of an input face sequence image, which utilize manually marker. The facial points were automatically tracked by a cross-correlation, which is based on optical flow,and then extracted the feature vectors. The mathematical model extracts features from the feature vectors. An ELMAN neural network was applied to classify expressions. The performances of the proposed facial expressions recognition were computed by Cohn-Kanade facial expressions database. This proposed approach achieved a high recognition rate.

Original languageEnglish
Title of host publicationAdvances in Neural Networks - ISNN 2009 - 6th International Symposium on Neural Networks, ISNN 2009, Proceedings
Number of pages8
EditionPART 3
Publication statusPublished - 2009
Event6th International Symposium on Neural Networks, ISNN 2009 - Wuhan, China
Duration: 2009 May 262009 May 29

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume5553 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other6th International Symposium on Neural Networks, ISNN 2009

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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