Facial Asymmetry Quantification for Expression Invariant Human Identification

  title={Facial Asymmetry Quantification for Expression Invariant Human Identification},
  author={Yanxi Liu and R. L. Weaver and Karen L. Schmidt and Jeffrey F. Cohn},
  journal={Computer Vision and Image Understanding},
We investigate facial asymmetry as a biometric under expression variation. For the first time, we have defined two types of quantified facial asymmetry measures that are easily computable from facial images and videos. Our findings show that the asymmetry measures of automatically selected facial regions capture individual differences that are relatively stable to facial expression variations. More importantly, a synergy is achieved by combining facial asymmetry information with conventional… CONTINUE READING

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