著者

松久 ひとみ 橋本 学

出版者

一般社団法人 映像情報メディア学会

雑誌

映像情報メディア学会誌 (ISSN:13426907)

巻号頁・発行日

vol.68, no.6, pp.J252-J255, 2014 (Released:2014-05-23)

参考文献数

10

被引用文献数

3

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Identifying subtle human facial expressions is important in human interactions such as human-robot communications. We propose a method to classify two types of facial expression, neutral (expressionless) and the subtle expression of happiness, using an image acquired with a camera. In the proposed method, facial shape features such as wrinkle-angle or unevenness of face surface are extracted via Gabor filters in multiple ROIs on a human face. High angle resolution Gabor filters are used to detect subtle facial expressions and the positions of the detection window and Gabor filter parameters are optimized by a learning process using AdaBoost. Changes to facial expression are estimated by comparing an input image to a learned database with the features. Experimental results showed that the proposed system has a 0.84 precision rate and a 0.91 recall rate in the case of detecting subtle changes.