Automatic Facial Expression Recognition with AAM-Based Feature Extraction and SVM Classifier

  • Xiaoyi Feng
  • Baohua Lv
  • Zhen Li
  • Jiling Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4293)


In this paper, an effective method is proposed for automatic facial expression recognition from static images. First, a modified Active Appearance Model (AAM) is used to locate facial feature points automatically. Then, based on this, facial feature vector is formed. Finally, SVM classifier with a sample selection method is adopted for expression classification. Experimental results on the JAFFE database demonstrate an average recognition rate of 69.9% for novel expressers, showing that the proposed method is promising.


Facial Expression Local Binary Pattern Expression Recognition Facial Expression Recognition Active Appearance Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xiaoyi Feng
    • 1
  • Baohua Lv
    • 1
  • Zhen Li
    • 1
  • Jiling Zhang
    • 1
  1. 1.School of Electronic and InformationNorthwestern Polytechnic UniversityXi’anChina

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