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An Improved LBP-based Facial Expression Recognition through Optimization of Block Weights

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2009, 14(11), pp.73-79
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

박성천 1 KOO JA YOUNG 1

1단국대학교

Accredited

ABSTRACT

In this paper, a method is proposed that enhances the performance of the facial expression recognition using template matching of Local Binary Pattern(LBP) histogram. In this method, the face image is segmented into blocks, and the LBP histogram is constructed to be used as the feature of the block. Block dissimilarity is calculated between a block of input image and the corresponding block of the model image. Image dissimilarity is defined as the weighted sum of the block dissimilarities. In conventional methods, the block weights are assigned by intuition. In this paper a new method is proposed that optimizes the weights from training samples. An experiment shows the recognition rate is enhanced by the proposed method.

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