Research on an Improved MB-LBP 3D Face Recognition Method

Liangliang Shi, Xia Wang, Yongliang Shen
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Abstract

In order to improve the accuracy and speed of 3D face recognition, this paper proposes an improved MB-LBP 3D face recognition method. First, the MB-LBP algorithm is used to extract the features of 3D face depth image, then the average information entropy algorithm is used to extract the effective feature information of the image, and finallythe Support Vector Machine algorithm is used to identify the extracted effective information. The recognition rate on the Texas 3DFRD database is 96.88%, and the recognition time is 0.025s. The recognition rate in the self-made depth library is 96.36%, and the recognition time is 0.02s.It can be seen from the experimental results that the algorithm in this paper has better performance in terms of accuracy and speed.
一种改进的MB-LBP三维人脸识别方法研究
为了提高三维人脸识别的精度和速度,本文提出了一种改进的MB-LBP三维人脸识别方法。首先利用MB-LBP算法提取三维人脸深度图像的特征,然后利用平均信息熵算法提取图像的有效特征信息,最后利用支持向量机算法对提取的有效信息进行识别。在Texas 3DFRD数据库上的识别率为96.88%,识别时间为0.025s。该深度库的识别率为96.36%,识别时间为0.02s。从实验结果可以看出,本文算法在准确率和速度上都有较好的表现。
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