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  • 标题:Facial Expression Analysis using Active Shape Model
  • 本地全文:下载
  • 作者:Reda Shbib ; Shikun Zhou
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2015
  • 卷号:8
  • 期号:1
  • 页码:9-22
  • DOI:10.14257/ijsip.2015.8.1.02
  • 出版社:SERSC
  • 摘要:Facial expressions analysis is a vital part of the research in human-machine interaction. This chapter introduces an automatic recognition system for facial expression from a front view human face image. Obtaining an effective facial representation from initial face images is an essential phase for strong and efficient facial expression system. In this chapter we have developed a facial expression analysis system. Firstly we have tried to evaluate facial analysis base on Active shape model (ASM). In order to detect the face images, Adaboost classifier and Haar-Like feature has been adopted to achieve face detection and tracking. The ASM then has been automatically initiated in the detected face image. Then, discriminates and reliable facial feature points has been extracted applying ASM fitting technique. The geometric displacement among the projected ASM feature points coordinates and the mean shape of ASM were used to evaluate facial expression. Using support vector machine (SVM) classifier, the obtained results has reached a recognition rate of 93 %.
  • 关键词:Facial Expression Recognition; Image processing
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