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Facial Expression Recognition Based on Perceived Facial Images and Local Feature Matching

  • Hayet Boughrara
  • Liming Chen
  • Chokri Ben Amar
  • Mohamed Chtourou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8157)

Abstract

Facial expression recognition is to determine the emotional state of the face regardless of its identity. Deriving an effective facial representation from original face images is a vital step for successful facial expression recognition. This paper presents a biological vision-based facial description, called Perceived Facial Images “PFI” applied to facial expression recognition. For the classification step, Scale Invariant Feature Transform “SIFT” is used to extract a local feature in images. Then, a matching computation is processed between a testing image and all train images for recognizing facial expression. To evaluate, the proposed approach is tested on the GEMEP FERA 2011 database and the Cohn-Kanade Facial Expression database. To compare, the developed algorithm achieves better experimental results than the other approaches in the literature.

Keywords

Facial Expression Recognition Feature extraction Perceived Facial Images “PFI” SIFT matching 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hayet Boughrara
    • 1
  • Liming Chen
    • 2
  • Chokri Ben Amar
    • 3
  • Mohamed Chtourou
    • 1
  1. 1.Control & Energy Management Laboratory, Sfax Engineering SchoolUniversity of SfaxSfaxTunisia
  2. 2.Laboratoire d’InfoRmatique en Image et Systémes d’information, Central School of LyonUniversity of LyonEcullyFrance
  3. 3.Research Group on Intelligent Machines, Sfax Engineering SchoolUniversity of SfaxSfaxTunisia

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