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Facial Expression Recognition Using 3D Facial Feature Distances

  • Hamit Soyel
  • Hasan Demirel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4633)

Abstract

In this paper, we propose a novel approach for facial expression analysis and recognition. The proposed approach relies on the distance vectors retrieved from 3D distribution of facial feature points to classify universal facial expressions. Neural network architecture is employed as a classifier to recognize the facial expressions from a distance vector obtained from 3D facial feature locations. Facial expressions such as anger, sadness, surprise, joy, disgust, fear and neutral are successfully recognized with an average recognition rate of 91.3%. The highest recognition rate reaches to 98.3% in the recognition of surprise.

Keywords

3D Facial Expression Analysis Facial Feature Points Neural Networks 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Hamit Soyel
    • 1
  • Hasan Demirel
    • 1
  1. 1.Department of Electrical and Electronic Engineering, Eastern Mediterranean University, Gazimağusa, KKTC, via Mersin 10Turkey

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