Facial action recognition for facial expression analysis from static face images
Facial action recognition for facial expression analysis from static face images
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DOI：
10.1109/tsmcb.2004.825931
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发表时间：
2004-06-01
影响因子：
--
通讯作者：
Rothkrantz, LJM
中科院分区：
文献类型：
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作者：
Pantic, M;Rothkrantz, LJM
面部动作的自动识别（即面部肌肉活动）正迅速成为机器视觉研究领域的一个热点。在本文中，我们提出了一个我们开发的自动化系统，用于识别静态，正面和/或侧面彩色面部图像中的面部手势。利用一种多检测器的人脸特征定位方法，对眼睛和嘴巴等面部成分的轮廓和轮廓进行空间采样。从提取的人脸特征轮廓中提取10个轮廓基点和19个人脸成分轮廓基点。基于这些，使用基于规则的推理识别单独或组合发生的32个单独的面部肌肉动作（au）。对于每个被评分的AU，所使用的算法关联一个因素，表示相关AU已被评分的确定性。实现了86%的识别率。
Automatic recognition of facial gestures (i.e., facial muscle activity) is rapidly becoming an area of intense interest in the research field of machine vision. In this paper, we present an automated system that we developed to recognize facial gestures in static, frontal- and/or profile-view color face images. A multidetector approach to facial feature localization is utilized to spatially sample the profile contour and the contours of the facial components such as the eyes and the mouth. From the extracted contours of the facial features, we extract ten profile-contour fiducial points and 19 fiducial points of the contours of the facial components. Based on these, 32 individual facial muscle actions (AUs) occurring alone or in combination are recognized using rule-based reasoning. With each scored AU, the utilized algorithm associates a factor denoting the certainty with which the pertinent AU has been scored. A recognition rate of 86% is achieved.