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Study of Video based Facial Expression and Emotions Recognition Methods

机译:基于视频的面部表情和情感识别方法的研究

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In real life scenario, facial expressions and emotions are nothing but responses to the external and internal events of human being. In human computer interaction, recognition of end user's expressions and emotions from the video streaming plays very important role. In such systems it is required to track the dynamic changes in human face movements quickly in order to deliver the required response system. The one real time application is physical fatigue detection based on facial detection and expressions such as driver fatigue detection in order to prevent the accidents on road. Face expression based physical fatigue analysis or detection is out of scope of this paper, but this paper reveal study on different methods those are presented recently for facial expression and/or emotions recognition using video. This paper presenting the methodologies in terms of feature extraction and classification used in facial expression and/or emotion recognition methods with their comparative study. The comparative study is done based on accuracy, implementation tool, advantages and disadvantages. The outcome of this paper is the current research gap and research challenges those are still open to solve for video based facial detection and recognition systems. The survey on recent methods is appropriately presented throughout this paper by considering future research works.
机译:在现实生活中,面部表情和情绪只不过是对人类的外部和内部事件的反应。在人类计算机互动中,对最终用户的表达和来自视频流的情感的识别起着非常重要的作用。在这种系统中,需要快速跟踪人脸移动中的动态变化,以便提供所需的响应系统。一个实时应用是基于面部检测的物理疲劳检测和诸如驾驶员疲劳检测的表达,以防止道路上的事故。基于面部表达的物理疲劳分析或检测超出了本文的范围,但本文揭示了利用视频的面部表情和/或情绪识别呈现的不同方法的研究。本文在具有对比例研究的面部表情和/或情感识别方法中使用的特征提取和分类方面呈现方法。比较研究是根据准确性,实施工具,优缺点进行的。本文的结果是目前的研究差距和研究挑战仍然可以开放,以解决基于视频的面部检测和识别系统。通过考虑未来的研究作品,在本文中对最近的方法进行了调查。

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