Please use this identifier to cite or link to this item: https://doi.org/10.1117/12.853220
Title: Feature selection for facial expression recognition using deformation modeling
Authors: Srivastava, R.
Sim, T. 
Yan, S. 
Ranganath, S. 
Keywords: Deformation modeling
Facial expression recognition
Feature extraction
Issue Date: 2010
Source: Srivastava, R., Sim, T., Yan, S., Ranganath, S. (2010). Feature selection for facial expression recognition using deformation modeling. Proceedings of SPIE - The International Society for Optical Engineering 7546. ScholarBank@NUS Repository. https://doi.org/10.1117/12.853220
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. © 2010 Copyright SPIE - The International Society for Optical Engineering.
Source Title: Proceedings of SPIE - The International Society for Optical Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/43300
ISBN: 9780819479426
ISSN: 0277786X
DOI: 10.1117/12.853220
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