Facial Expression Recognition Based on Facial Region Segmentation and Modal Value Approach

Gibran BENITEZ-GARCIA  Gabriel SANCHEZ-PEREZ  Hector PEREZ-MEANA  Keita TAKAHASHI  Masahide KANEKO  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E97-D   No.4   pp.928-935
Publication Date: 2014/04/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E97.D.928
Type of Manuscript: PAPER
Category: Image Recognition, Computer Vision
Keyword: 
facial expression recognition,  partial occlusion,  facial segmentation,  modal value,  

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Summary: 
This paper presents a facial expression recognition algorithm based on segmentation of a face image into four facial regions (eyes-eyebrows, forehead, mouth and nose). In order to unify the different results obtained from facial region combinations, a modal value approach that employs the most frequent decision of the classifiers is proposed. The robustness of the algorithm is also evaluated under partial occlusion, using four different types of occlusion (half left/right, eyes and mouth occlusion). The proposed method employs sub-block eigenphases algorithm that uses the phase spectrum and principal component analysis (PCA) for feature vector estimation which is fed to a support vector machine (SVM) for classification. Experimental results show that using modal value approach improves the average recognition rate achieving more than 90% and the performance can be kept high even in the case of partial occlusion by excluding occluded parts in the feature extraction process.