Facial Expression Recognition Based on Texture Features

Alaa Nabeel Haj Najeb, N. Nasser
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引用次数: 0

Abstract

Facial expressions are a form of non-verbal communication, they appear as changes on the surface of the facial skin according to one's inner emotional states, aims, or social communications. Classification of these expressions is a normal process for humans, but it is a challenging task for machines.Lately, interest in facial expression recognition has grown, and many systems have been developed to classify expressions from facial images. Any expression recognition system is comprised of three steps. The first one is face acquisition, then feature extraction, and finally classification. The classification accuracy depends primarily on the feature extraction step.  Therefore, in this research we study many texture feature extraction descriptors and compare their results under the same preprocessing circumstances; moreover, we propose two improvements for one of these descriptors, which give better results than the original one. We validate the results on two commonly used databases for expression recognition using Matlab programming language, wishing all of that to be an interesting point for researchers in this field.
基于纹理特征的面部表情识别
面部表情是一种非语言交流的形式,它表现为面部皮肤表面的变化,根据一个人的内心情绪状态、目的或社会交往而变化。对这些表达进行分类对人类来说是一个正常的过程,但对机器来说是一项具有挑战性的任务。近年来,人们对面部表情识别的兴趣越来越大,并且开发了许多系统来从面部图像中分类表情。任何表情识别系统都由三个步骤组成。首先是人脸采集,然后是特征提取,最后是分类。分类精度主要取决于特征提取步骤。因此,在本研究中,我们研究了多种纹理特征提取描述符,并比较了它们在相同预处理条件下的提取结果;此外,我们对其中一个描述符提出了两个改进,得到了比原始描述符更好的结果。我们使用Matlab编程语言在两种常用的表情识别数据库上验证了结果,希望这一切都能成为该领域研究人员的一个有趣的点。
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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