Facial Expression Recognition for E-learning Systems using Gabor Wavelet & Neural Network
Facial Expression Recognition for E-learning Systems using Gabor Wavelet & Neural Network
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DOI：
10.1109/icalt.2006.171
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发表时间：
2006-07
期刊：
影响因子：
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通讯作者：
May-Ping Loh;Ya-Ping Wong;Chee-Onn Wong
中科院分区：
文献类型：
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作者：
May-Ping Loh;Ya-Ping Wong;Chee-Onn Wong
本文介绍了利用Gabor小波进行人脸特征提取，利用BP神经网络进行表情分类的e学习人脸表情识别的初步研究和取得的成果。建立了一个包含600幅人脸表情图像的eFEC数据库。我们还提供了为什么我们需要建立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。你可以在呈现的各种实验结果中找到比较。我们相信，这些信息将非常有用，为如何提高系统性能并使其适用于现实的电子学习环境提供指导和指导。(缩写：eFEC--学习面部表情分类；CCA--平均正确分类)
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)