Facial Expression Recognition: A Review of Methods, Performances and Limitations

Olufisayo S. Ekundayo, Serestina Viriri
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引用次数: 17

Abstract

Facial expression is one of the profound nonverbal channels through which human emotion state is communicated, its automation involves analysis and recognition of facial features. Facial Expression Recognition (FER) is categorized as behavioral biometrics, and also applicable in the field of computer vision and human computer interaction. Variations in the nature of the images to be processed; head pose, image background, light intensity and occlusion are some of the sources of the challenges with facial expression recognition system. Achieving a robust automatic facial expression recognition system invariant to the aforementioned challenges, is the goal of this research area. This paper presents an analysis of major feature extraction and classification methods, their performances in terms of accuracy and their respective limitations.
面部表情识别:方法、性能和局限性的综述
面部表情是人类情感状态交流的深层非语言渠道之一,其自动化涉及对面部特征的分析和识别。面部表情识别(FER)是一种行为生物识别技术,在计算机视觉和人机交互领域也有广泛的应用。待处理图像性质的变化;头部姿态、图像背景、光线强度和遮挡是人脸表情识别系统面临的挑战。实现一个鲁棒的面部表情自动识别系统是本研究领域的目标。本文分析了主要的特征提取和分类方法,以及它们在准确率方面的表现和各自的局限性。
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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