基于曲率局部二值模式的三维面部表情识别

Yiding Wang, Meng Meng
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引用次数: 6

摘要

提出了一种基于曲率的LBP特征自动识别三维面部表情的方法。三维面部表情图像采用四幅图像进行描述,灰度值为基于曲率的描述子(主曲率k1、k2、平均曲率、形状指数)的值,然后进行LBP编码。为了有效地优化性能,使用卡方距离进行分类。最后,在博斯普鲁斯数据库上的实验结果表明,基于曲率的LBP (CLBP)比其他特征具有更好的性能,也表明这些特征对3D面部表情识别具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3D Facial Expression Recognition on Curvature Local Binary Patterns
This paper proposed a new method Based on curvature Based LBP feature to recognize 3D facial expression automatically. 3D facial expression images are described by means of four images which gray level are the value of curvature-Based descriptors (principal curvatures k1, k2, mean curvature, shape index) and then encoded by LBP. To efficiently optimize the performance, Chi-square distance is employed for classification. Finally, experimental result achieved on the Bosphorus database illustrates that the curvature-Based LBP (CLBP) has performs better than other features and also shows these features are significant for 3D facial expression recognition.
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