Shen Wei, Ding Rong, Zhang Huiet al. Study on H.323-based distributed gatekeepers[J]. Journal of Beijing University of Aeronautics and Astronautics, 2007, 33(01): 55-58. (in Chinese)
Citation: Xue Yuli, Mao Xia, Caleanu Catalin-Daniel, et al. Robust facial expression recognition under occlusion condition[J]. Journal of Beijing University of Aeronautics and Astronautics, 2010, 36(4): 429-433. (in Chinese)

Robust facial expression recognition under occlusion condition

  • Received Date: 16 Mar 2009
  • Publish Date: 30 Apr 2010
  • A novel method for facial expression recognition which is robust to facial occlusion was proposed. Firstly, the face to be recognized is reconstructed using robust principal component analysis(RPCA), and saliency detection was used on the difference image of reconstructed face and the face to be recognized to obtain the facial occlusion region. Secondly, facial occlusion region of the face to be recognized was reconstructed by the reconstructed face using RPCA, and a novel reweighted AdaBoost classifier was used on the face after occlusion region reconstruction for facial expression recognition. Finally, facial expression recognition experiments were implemented in different occlusion conditions on Beihang university(BHU) facial expression database and Japanese female facial expression database and gained better recognition results than Adaboost method, showing that this method based on RPCA and AdaBoost is robust to kinds of facial occlusions.

     

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