Journal of Systems Engineering and Electronics ›› 2010, Vol. 21 ›› Issue (1): 118-126.doi: 10.3969/j.issn.1004-4132.2010.01.019

• SOFTWARE ALGORITHM AND SIMULATION • Previous Articles     Next Articles

Person-independent expression recognition based on person-similarity weighted expression feature

Huachun Tan1,∗, Yujin Zhang2, Hao Chen1, Yanan Zhao1, and Wuhong Wang1   

  • Online:2010-02-26 Published:2010-01-03
  • Supported by:

    This work was supported by National Natural Science Foundation of China (60872084; 60940008), Beijing Training Programming Foundation for the Talents (20081D1600300343), Excellent Young Scholar Research Fund of Beijing Institute of Technology (2007Y0305), Fundamental Research Foundation of Beijing Institute of Technology (20080342005).


A new method to extract person-independent expression feature based on higher-order singular value decomposition (HOSVD) is proposed for facial expression recognition. Based on the assumption that similar persons have similar facial expression appearance and shape, the person-similarity weighted expression feature is proposed to estimate the expression feature of test persons. As a result, the estimated expression feature can reduce the influence of individuals caused by insufficient training data, and hence become less person-dependent. The proposed method is tested on Cohn-Kanade facial expression database and Japanese female facial expression (JAFFE) database. Person-independent experimental results show the superiority of the proposed method over the existing methods.