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Robust facial expression recognition based on RPCA and AdaBOOST

  • Xia Mao*
  • , Yu Li Xue
  • , Zheng Li
  • , Kang Huang
  • , Shan Wei Lv
  • *Corresponding author for this work
  • Beihang University

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

Abstract

In this paper, we consider the problem of robust facial expression recognition and propose a novel scheme for facial expression recognition under facial occlusion. There are two main contributions in this work. Firstly, a novel method for facial occlusion detection based on robust principal component analysis (RPCA) and saliency detection performs efficiently to detect facial occlusions. Secondly, a novel method based on occlusion reconstruction and reweighted AdaBoost classification is prosed for facial expression recognition. Experimental results have shown the effectiveness of our proposed method for robust facial expression recognition.

Original languageEnglish
Title of host publication2009 10th International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS 2009
Pages113-116
Number of pages4
DOIs
StatePublished - 2009
Event2009 10th International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS 2009 - London, United Kingdom
Duration: 6 May 20098 May 2009

Publication series

Name2009 10th International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS 2009

Conference

Conference2009 10th International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS 2009
Country/TerritoryUnited Kingdom
CityLondon
Period6/05/098/05/09

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