人脸检测与表情分类技术研究

G. Hemalatha, C. Sumathi, Manonmaniam Sundaranar
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引用次数: 67

摘要

面部表情的自动识别是人机界面的重要组成部分。自20世纪90年代以来,它在研究领域引起了很大的关注。虽然人类可以毫不费力地识别人脸,但机器的识别仍然是一个挑战。它的一些挑战是高度动态的方向,照明,规模,面部表情和遮挡。应用领域包括用户认证、身份识别、视频监控、信息安全、数据隐私等。人脸识别的各种方法可分为基于整体的人脸识别和基于特征的人脸识别两种。基于整体的方法是将图像数据作为一个整体来处理,而不是将人脸中的不同区域隔离开来。基于特征的方法是识别人脸上的某些点,如眼睛、鼻子和嘴巴等。本文从人脸检测、人脸特征提取和分类等方面对人脸表情识别进行了分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study of Techniques for Facial Detection and Expression Classification
Automatic recognition of facial expressions is an important component for human-machine interfaces. It has lot of attraction in research area since 1990's.Although humans recognize face without effort or delay, recognition by a machine is still a challenge. Some of its challenges are highly dynamic in their orientation, lightening, scale, facial expression and occlusion. Applications are in the fields like user authentication, person identification, video surveillance, information security, data privacy etc. The various approaches for facial recognition are categorized into two namely holistic based facial recognition and feature based facial recognition. Holistic based treat the image data as one entity without isolating different region in the face where as feature based methods identify certain points on the face such as eyes, nose and mouth etc. In this paper, facial expression recognition is analyzed with various methods of facial detection,facial feature extraction and classification.
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