EigenExpress Approach in Recognition of Facial Expression Using GPU

  • Qi Wu
  • Mingli Song
  • Jiajun Bu
  • Chun Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3979)


The automatic recognition of facial expression presents a significant challenge to the pattern analysis and man-machine interaction research community. In this paper, a novel system is proposed to recognize human facial expressions based on the expression sketch. Firstly, facial expression sketch is extracted by an GPU-based real-time edge detection and sharpening algorithm from original gray image. Then, a statistical method, which is called Eigenexpress, is introduced to obtain the expression feature vectors for sketches. Finally, Modified Hausdorff distance(MHD) was used to perform the expression classification. In contrast to performing feature vector extraction from the gray image directly, the sketch based expression recognition reduces the feature vector’s dimension first, which leads to a concise representation of the facial expression. Experiment shows our method is appreciable and convincible.


Facial Expression Graphic Process Unit Expression Recognition Facial Expression Recognition Graphic Hardware 
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

  • Qi Wu
    • 1
  • Mingli Song
    • 1
  • Jiajun Bu
    • 1
  • Chun Chen
    • 1
  1. 1.College of Computer ScienceZhejiang UniversityHangzhouPR China

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