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Face Recognition for Expressive Face Images

机译:表情人脸图像的人脸识别

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摘要

In this paper, we deal with a face recognition method for the expressive face images. Since the face recognition is one of the most natural and straightforward biometric methods, there have been various research works. However, most of them are focused on the expressionless face images. In real situations, however, it is required to consider the emotional face images. Here, three basic human emotions such as happiness, sadness, and anger are investigated. The face recognition becomes a very difficult problem if we consider the facial expression. This situation requires a robust face recognition algorithm. So, we use a fuzzy linear discriminant (LDA) algorithm with the wavelet transform. The fuzzy LDA is a statistical method that maximizes the ratio of between-scatter matrix and within-scatter matrix and also handles the fuzzy class information.
机译:在本文中,我们研究了一种用于表情人脸图像的人脸识别方法。由于面部识别是最自然,最直接的生物特征识别方法之一,因此已经进行了各种研究工作。然而,它们大多数集中在无表情的面部图像上。然而,在实际情况下,需要考虑情绪面部图像。在这里,研究了人类的三种基本情感,例如幸福,悲伤和愤怒。如果考虑面部表情,面部识别就成为一个非常困难的问题。这种情况需要鲁棒的人脸识别算法。因此,我们在小波变换中使用模糊线性判别(LDA)算法。模糊LDA是一种统计方法,它使散点间矩阵与散点内矩阵之比最大化,并且还处理模糊类信息。

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