Emotion recognition by face dynamics

Svetoslav Nedkov, D. Dimov
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引用次数: 4

Abstract

The paper proposes an accessible method for emotion recognition from facial dynamics in video streams. The emotions considered are anger, disgust, fear, happiness, sadness, surprise, and the neutral expression as well. The method is based on the Facial Action Coding System (FACS) that regards individual action units (AU) as features for the recognition of emotions. On the basis of FACS we propose an a'priori juxtaposition between the well known Candide model vertexes and the landmarks selected in each individual video frame with human face. We use a Linear Discriminant Analysis (LDA) approach to define an emotion classifier. To this end our approach is facilitated by some assumptions like the need of well defined start and peak frames for each emotion under recognition. The experiments show that the method we propose can be successfully further developed for most of the real cases of face emotion recognition.
基于面部动态的情绪识别
本文提出了一种基于视频流中面部动态的情感识别方法。考虑的情绪包括愤怒、厌恶、恐惧、快乐、悲伤、惊讶和中性的表情。该方法基于面部动作编码系统(FACS),该系统将个体动作单元(AU)作为识别情绪的特征。在FACS的基础上,我们提出了将已知的Candide模型顶点与每个带有人脸的单独视频帧中选择的地标并置的先验方法。我们使用线性判别分析(LDA)方法来定义情感分类器。为此,我们的方法通过一些假设来促进,比如需要为识别中的每种情绪定义良好的开始帧和峰值帧。实验表明,我们提出的方法可以成功地进一步发展,适用于大多数真实的人脸情感识别案例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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