首页> 外文会议>International Conference on Affective Computing and Intelligent Interaction(ACII 2005); 20051022-24; Beijing(CN) >Real-Time Facial Expression Recognition System Based on HMM and Feature Point Localization
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Real-Time Facial Expression Recognition System Based on HMM and Feature Point Localization

机译:基于HMM和特征点定位的实时面部表情识别系统

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摘要

It is difficult for computer to recognize facial expression in realtime. Until now, no good method is put forward to solve this problem in and abroad. In this paper, we present an effective automated system that we developed to recognize facial gestures in real-time. According to psychologists' facial expression classification, we define four basic facial expressions and localize key facial feature points exactly then extract facial components' contours. We analyze and record facial components' movements using information in sequential frames to recognize facial gestures. Since different facial expressions can have some same movements, it is necessary to use a good facial expression model to describe the relation between expression states and observed states of facial components' movements for achieving a good recognition results. HMM is such a good method which can meet our requirement. We present a facial expression model based on HMM and get good real-time recognition results.
机译:计算机很难实时识别面部表情。迄今为止,国内外都没有提出解决这一问题的好方法。在本文中,我们提出了一个有效的自动化系统,我们开发了该系统以实时识别面部手势。根据心理学家的面部表情分类,我们定义了四个基本面部表情并精确定位关键的面部特征点,然后提取面部成分的轮廓。我们使用顺序帧中的信息来分析和记录面部组件的运动,以识别面部手势。由于不同的面部表情可以具有相同的运动,因此有必要使用良好的面部表情模型来描述表情状态与面部组件运动的观察状态之间的关系,以实现良好的识别结果。 HMM是一种可以满足我们要求的好方法。我们提出了一种基于HMM的面部表情模型,并获得了良好的实时识别结果。

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