基于数据挖掘的面部表情识别系统

Hazar Mliki, Nesrine Fourati, Mohamed Hammami, H. Ben-Abdallah
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引用次数: 8

摘要

本文介绍了一种新的面部表情分析系统,该系统能够自动识别面部表情,管理面部表情强度的变化,减少面部表情类别之间的怀疑和混淆。本文提出了一种利用向量场卷积(VFC)技术高效分割人脸特征轮廓的新方法。根据检测到的轮廓图,提取与面部表情变形相关的面部特征点。然后通过数据挖掘技术建立了一组检测点之间的距离模型来定义预测规则。通过实验研究,评估了该方案在不同因素下的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Mining-based Facial Expressions Recognition System
In this paper, we introduce a new facial-expression analysis system designed to automatically recognize facial expressions, able to manage facial-expression intensity variation as well as reducing the doubt and confusion between facial-expression classes. Our proposed approach introduces a new method to segment efficiently facial feature contours using Vector Field Convolution (VFC) technique. Relying on the detected con- tours, we extract facial feature points which go with facial-expression deformations. Then we have modeled a set of distances among the detected points to define prediction rules through data mining technique. An experimental study was conducted to evaluate the per- formance of our proposed solution under varying factors.
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