Integrated Expression-Invariant Face Recognition with Constrained Optical Flow

  • Chao-Kuei Hsieh
  • Shang-Hong Lai
  • Yung-Chang Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5414)

Abstract

Face recognition is one of the most intensively studied topics in computer vision and pattern recognition. A constrained optical flow algorithm, which combines the advantages of the unambiguous correspondence of feature point labeling and the flexible representation of optical flow computation, has been proposed in our pervious work for face recognition from expressional face images. In this paper, we propose an integrated face recognition system that is robust against facial expressions by combining information from the computed intra-person optical flow and the synthesized face image in a probabilistic framework. Our experimental results show that the proposed system improves the accuracy of face recognition from expressional face images.

Keywords

Face recognition expression recognition constrained optical flow expression normalization 

References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Chao-Kuei Hsieh
    • 1
  • Shang-Hong Lai
    • 2
  • Yung-Chang Chen
    • 1
  1. 1.Department of Electrical EngineeringNational Tsing Hua UniversityTaiwan
  2. 2.Department of Computer ScienceNational Tsing Hua UniversityTaiwan

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