Expression recognition using fuzzy spatio-temporal modeling

T. Xiang, M. K.H. Leung, S. Y. Cho

Research output: Journal PublicationArticlepeer-review

35 Citations (Scopus)


In human-computer interaction, there is a need for computer to recognize human facial expression accurately. This paper proposes a novel and effective approach for facial expression recognition that analyzes a sequence of images (displaying one expression) instead of just one image (which captures the snapshot of an emotion). Fourier transform is employed to extract features to represent an expression. The representation is further processed using the fuzzy C means computation to generate a spatio-temporal model for each expression type. Unknown input expressions are matched to the models using the Hausdorff distance to compute dissimilarity values for classification. The proposed technique has been tested with the CMU expression database, generating superior results as compared to other approaches.

Original languageEnglish
Pages (from-to)204-216
Number of pages13
JournalPattern Recognition
Issue number1
Publication statusPublished - Jan 2008
Externally publishedYes


  • Facial expression
  • Fourier transform
  • Fuzzy C means
  • HCI
  • Hausdorff distance
  • Spatio-temporal

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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