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Facial Expression Recognition Using Extended Local Binary Patterns of 3D Curvature

  • Soon-Yong Chun
  • Chan-Su Lee
  • Sang-Heon Lee
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 240)

Abstract

This paper presents extended local binary patterns (LBP) for facial expression analysis from 3D depth map images. Recognition of facial expressions is important to understand human emotion and develop affective human computer interaction. LBP and its extensions are frequently used for texture classification and face identification and detection. In the 3D surface analysis, curvature is very important characteristics. This paper presents an extension of LBP for modeling curvature from 3D depth map images. The extended curvature LBP (CLBP) is used for facial expression recognition. Experimental results using Bosphorus facial expression database show better performance by 3D curvature and the combination of 3D curvature and 2D images than by conventional 2D or 2D + 3D approaches.

Notes

Acknowledgments

This work was supported by the DGIST R&D Program of the Ministry of Education, Science and Technology of Korea (13-IT-03).

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Copyright information

© Springer Science+Business Media Dordrecht(Outside the USA) 2013

Authors and Affiliations

  • Soon-Yong Chun
    • 1
  • Chan-Su Lee
    • 1
  • Sang-Heon Lee
    • 2
  1. 1.Department of Electronic EngineeringYeungnam UniversityGyeongsangbook-doKorea
  2. 2.Daegu Gyeongbuk Institute of Science and TechnologyDaeguKorea

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