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A novel fuzzy facial expression recognition system based on facial feature extraction from color face images

机译:基于彩色人脸图像人脸特征提取的新型模糊人脸表情识别系统

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摘要

Emotion recognition plays an effective and important role in Human-Computer Interaction (HCI). Recently, various approaches to emotion recognition have been proposed in the literature, but they do not provide a powerful approach to recognize emotions from Partially Occluded Facial Images.In this paper, we propose a new method for Emotion Recognition from Facial Expression using Fuzzy Inference System (FIS). This novel method is even able to recognize emotions from Partially Occluded Facial Images. Moreover, this research describes new algorithms for facial feature extraction that demonstrate satisfactory performance and precision. In addition, one of the main factors that have an important influence on the final precision of fuzzy inference systems is the membership function parameters. Therefore, we use a Genetic Algorithm for parameter-tuning of the membership functions. Experimental results report an average precision rate of 93.96% for Emotion Recognition of six basic emotions, which is so promising.
机译:情绪识别在人机交互(HCI)中起着有效而重要的作用。近年来,文献中提出了多种情绪识别方法,但是它们并不能为部分遮挡的人脸图像中的情绪识别提供有效的方法。本文提出了一种基于模糊推理系统的人脸表情识别方法。 (FIS)。这种新颖的方法甚至能够从部分遮挡的面部图像中识别出情绪。此外,本研究描述了用于面部特征提取的新算法,该算法表现出令人满意的性能和精度。另外,隶属函数参数是影响模糊推理系统最终精度的重要因素之一。因此,我们使用遗传算法对隶属函数进行参数调整。实验结果表明,对六种基本情绪的情感识别的平均准确率达到93.96%,这是很有希望的。

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