Facial Expression Recognition for E-learning Systems using Gabor Wavelet & Neural Network

May-Ping Loh, Ya-Ping Wong, Chee-Onn Wong
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引用次数: 21

Abstract

In this paper, we present our initial studies and results obtained on e-learning facial expression recognition using Gabor Wavelet for facial feature extraction, and Back-propagation Neural Network for expression classification. An eFEC database that consists of 600 facial expression images is built for our research. We also provide reasons on why we need to build our own database instead of customizing and use current available expressions database, and what are the differences between eFEC databases compared with others. You may find comparisons in various experiment results presented. We believe the information would be very useful as to provide guideline and direction on how to improve the system performance and make it applicable in real-life elearning environments. (Abbreviation: eFEC --learning Facial Expression Classification; cca - correct classification in average)
基于Gabor小波和神经网络的电子学习系统面部表情识别
在本文中,我们介绍了我们在电子学习面部表情识别方面的初步研究和结果,使用Gabor小波进行面部特征提取,并使用反向传播神经网络进行表情分类。本文建立了一个包含600张面部表情图像的eFEC数据库。我们还提供了为什么我们需要构建自己的数据库而不是定制和使用当前可用的表达式数据库的原因,以及eFEC数据库与其他数据库的区别。你可以在不同的实验结果中找到比较。我们相信这些信息将非常有用,可以为如何提高系统性能并使其适用于现实生活中的电子学习环境提供指导和方向。(简称:eFEC——学习面部表情分类;Cca -正确的平均分类)
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