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Proceedings Paper

Feature selection for facial expression recognition using deformation modeling
Author(s): Ruchir Srivastava; Terence Sim; Shuicheng Yan; Surendra Ranganath
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Paper Abstract

Works on Facial Expression Recognition (FER) have mostly been done using image based approaches. However, in recent years, researchers have also been trying to explore the use of 3D information for the task of FER. Most of the time, there is a need for having a neutral (expressionless) face of the subject in both the image based and 3D model based approaches. However, this might not be practical in many applications. This paper tries to address this limitations in previous works by proposing a novel technique of feature extraction which does not require any neutral face of the subjects. It has been proposed and validated experimentally that the motion of some landmark points on the face, in exhibiting a particular facial expression, is similar in different persons. Separate classifier is made and relevant feature points are selected for each expression. One vs all SVM classification gives promising results.

Paper Details

Date Published: 26 February 2010
PDF: 6 pages
Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75462A (26 February 2010); doi: 10.1117/12.853220
Show Author Affiliations
Ruchir Srivastava, National Univ. of Singapore (Singapore)
Terence Sim, National Univ. of Singapore (Singapore)
Shuicheng Yan, National Univ. of Singapore (Singapore)
Surendra Ranganath, National Univ. of Singapore (Singapore)


Published in SPIE Proceedings Vol. 7546:
Second International Conference on Digital Image Processing
Kamaruzaman Jusoff; Yi Xie, Editor(s)

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