计算机科学 ›› 2011, Vol. 38 ›› Issue (4): 25-31.

• 综述 • 上一篇    下一篇

人脸表情识别的研究进展

蒋斌,贾克斌,杨国胜   

  1. (北京工业大学电子信息与控制工程学院 北京100124);(中央民族大学信息工程学院 北京100081)
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金项目(30970780)资助。

Research Advance of Facial Expression Recognition

JIANG Bin,JIA Ke-bin,YANG Guo-sheng   

  • Online:2018-11-16 Published:2018-11-16

摘要: 人脸表情识别是人机交互、机器学习、智能控制和图像处理等领域涉及的重要研究方向,目前已成为国内外研究的热点。从人脸表情识别的特征提取和特征分类两方面出发,总结了国内外近几年人脸表情识别的进展状况。在特征提取阶段,根据所处理的图像的属性,分别从静态图像和动态图像两个方面总结人脸表情的特征提取算法,前者包括整体法和局部法,后者分为模型法、光流法和几何法。在分类器的设计上,以贝叶斯网络和距离度量两条理论主线,贯穿主要的方法。最后结合国内外最新的研究成果和应用领域,展望了人脸表情识别的发展。

关键词: 人脸表情识别,特征提取,特征分类

Abstract: In recent years, facial expression recognition has become a hot research direction in human computer interaction,machine learning,intelligent control and image processing. According to feature extraction and feature classification, recent developments of facial expression recognition were presented. From static images and image sequences, the methods of feature extraction can be divided into two categories. The former includes holistic methods and local methods, the later includes templatcbased methods, geometry-based methods and optical flow methods. In the classifier design, the main methods of feature classification can be categorized by Bayesian Network methods and Distance Metric methods. Finally, combining the latest productions and applications at home and abroad, the expectation of the development of facial expression recognition was given.

Key words: Facial aexpression recognition, Feature extraction, Feature classification

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