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Selecting, Optimizing and Fusing ‘Salient’ Gabor Features for Facial Expression Recognition

  • Ligang Zhang
  • Dian Tjondronegoro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5863)

Abstract

This paper describes a novel framework for facial expression recognition from still images by selecting, optimizing and fusing ‘salient’ Gabor feature layers to recognize six universal facial expressions using the K nearest neighbor classifier. The recognition comparisons with all layer approach using JAFFE and Cohn-Kanade (CK) databases confirm that using ‘salient’ Gabor feature layers with optimized sizes can achieve better recognition performance and dramatically reduce computational time. Moreover, comparisons with the state of the art performances demonstrate the effectiveness of our approach.

Keywords

Facial expression recognition Gabor filter (2D)2PCA KNN 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Ligang Zhang
    • 1
  • Dian Tjondronegoro
    • 1
  1. 1.Faculty of Science and TechonoglyQueensland University of TechonoglyBrisbaneAustralia

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