Facial expression recognition on hexagonal structure using LBP-based histogram variances

Lin Wang, Xiangjian He, Ruo Du, Wenjing Jia, Qiang Wu, Wei Chang Yeh

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)


In our earlier work, we have proposed an HVF (Histogram Variance Face) approach and proved its effectiveness for facial expression recognition. In this paper, we extend the HVF approach and present a novel approach for facial expression. We take into account the human perspective and understanding of facial expressions. For the first time, we propose to use the Local Binary Pattern (LBP) defined on the hexagonal structure to extract local, dynamic facial features from facial expression images. The dynamic LBP features are used to construct a static image, namely Hexagonal Histogram Variance Face (HHVF), for the video representing a facial expression. We show that the HHVFs representing the same facial expression (e.g., surprise, happy and sadness etc.) are similar no matter if the performers and frame rates are different. Therefore, the proposed facial recognition approach can be utilised for the dynamic expression recognition. We have tested our approach on the well-known Cohn-Kanade AU-Coded Facial Expression database. We have found the improved accuracy of HHVF-based classification compared with the HVF-based approach.

Original languageEnglish
Title of host publicationAdvances in Multimedia Modeling - 17th International Multimedia Modeling Conference, MMM 2011, Proceedings
Number of pages11
EditionPART 2
Publication statusPublished - 2011
Externally publishedYes
Event17th Multimedia Modeling Conference, MMM 2011 - Taipei, Taiwan, Province of China
Duration: 5 Jan 20117 Jan 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6524 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference17th Multimedia Modeling Conference, MMM 2011
Country/TerritoryTaiwan, Province of China


  • Action Unit
  • Hexagonal structure
  • Histogram Variance Face
  • PCA
  • SVM

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)


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