Facial Micro-Expression Detection in Hi-Speed Video Based on Facial Action Coding System (FACS)
Facial Micro-Expression Detection in Hi-Speed Video Based on Facial Action Coding System (FACS)
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DOI：
10.1587/transinf.e96.d.81
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发表时间：
2013-01-01
影响因子：
0.7
通讯作者：
Ohta, Yuichi
中科院分区：
文献类型：
--
作者：
Polikovsky, Senya;Kameda, Yoshinari;Ohta, Yuichi
面部微表情是快速而微妙的面部运动，被认为是检测一个人隐藏的情绪变化的最有用的外部标志之一。然而，它们不容易检测和测量，因为它们只出现很短的时间，在面部区域没有显著特征的肌肉收缩很小。提出了一种新的计算机视觉方法来检测和测量面部微表情的时序特征。这种方法的核心是基于一个描述符，结合预处理掩模，直方图和级联的时空梯度矢量。提出的三维梯度直方图描述子能够检测和测量面部皮肤表面快速而细微变化的时序特征。该方法专门设计用于分析使用高速200 fps相机记录的视频。微表情的最终分类是通过使用k均值分类器和投票程序来完成的。在我们新的高速微表情视频数据库中，面部动作编码系统被用来注释表情的外观和动态。使用我们新的高速视频数据库验证了所提出的方法的效率。
Facial micro-expressions are fast and subtle facial motions that are considered as one of the most useful external signs for detecting hidden emotional changes in a person. However, they are not easy to detect and measure as they appear only for a short time, with small muscle contraction in the facial areas where salient features are not available. We propose a new computer vision method for detecting and measuring timing characteristics of facial micro-expressions. The core of this method is based on a descriptor that combines pre-processing masks, histograms and concatenation of spatial-temporal gradient vectors. Presented 3D gradient histogram descriptor is able to detect and measure the timing characteristics of the fast and subtle changes of the facial skin surface. This method is specifically designed for analysis of videos recorded using a hi-speed 200 fps camera. Final classification of micro expressions is done by using a k-mean classifier and a voting procedure. The Facial Action Coding System was utilized to annotate the appearance and dynamics of the expressions in our new hi-speed micro-expressions video database. The efficiency of the proposed approach was validated using our new hi-speed video database.