Bartlett M S, Hager J C, Ekman P, Sejnowski T J
Department of Cognitive Science, University of California, San Diego, USA.
Psychophysiology. 1999 Mar;36(2):253-63. doi: 10.1017/s0048577299971664.
Facial expressions provide an important behavioral measure for the study of emotion, cognitive processes, and social interaction. The Facial Action Coding System (Ekman & Friesen, 1978) is an objective method for quantifying facial movement in terms of component actions. We applied computer image analysis to the problem of automatically detecting facial actions in sequences of images. Three approaches were compared: holistic spatial analysis, explicit measurement of features such as wrinkles, and estimation of motion flow fields. The three methods were combined in a hybrid system that classified six upper facial actions with 91% accuracy. The hybrid system outperformed human nonexperts on this task and performed as well as highly trained experts. An automated system would make facial expression measurement more widely accessible as a research tool in behavioral science and investigations of the neural substrates of emotion.
面部表情为研究情绪、认知过程和社会互动提供了一项重要的行为测量方法。面部动作编码系统（埃克曼和弗里森，1978年）是一种根据组成动作对面部运动进行量化的客观方法。我们将计算机图像分析应用于自动检测图像序列中面部动作的问题。比较了三种方法：整体空间分析、对皱纹等特征的明确测量以及运动流场估计。这三种方法被整合到一个混合系统中，该系统对六种上部面部动作的分类准确率达到了91%。在这项任务中，该混合系统的表现优于非专业人员，与训练有素的专家相当。一个自动化系统将使面部表情测量作为行为科学研究工具以及情绪神经基础研究工具得到更广泛的应用。
