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http://dx.doi.org/10.9717/kmms.2013.16.12.1357

A Study on Facial Expression Recognition using Boosted Local Binary Pattern  

Won, Chulho (경일대학교 첨단의료기학과)
Publication Information
Journal of Korea Multimedia Society / v.16, no.12, 2013 , pp. 1357-1367 More about this Journal
Abstract
Recently, as one of images based methods in facial expression recognition, the research which used ULBP block histogram feature and SVM classifier was performed. Due to the properties of LBP introduced by Ojala, such as highly distinction capability, durability to the illumination changes and simple operation, LBP is widely used in the field of image recognition. In this paper, we combined $LBP_{8,2}$ and $LBP_{8,1}$ to describe micro features in addition to shift, size change in calculating ULBP block histogram. From sub-windows of 660 of $LBP_{8,1}$ and 550 of $LBP_{8,2}$, ULBP histogram feature of 1210 were extracted and weak classifiers of 50 were generated using AdaBoost. By using the combined $LBP_{8,1}$ and $LBP_{8,2}$ hybrid type of ULBP histogram feature and SVM classifier, facial expression recognition rate could be improved and it was confirmed through various experiments. Facial expression recognition rate of 96.3% by hybrid boosted ULBP block histogram showed the superiority of the proposed method.
Keywords
Local binary pattern; Facial Expression;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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