基于深度数据的三维人脸识别

3D face recognition based on depth data

为了进一步提高三维人脸识别效率,在Fisherface和局部二值模式(LBP)的基础上,提出了基于深度数据的三维人脸识别方法:先提取人脸的深度数据,再将深度数据与LBP相结合提取人脸特征,然后采用Fisherface方法进行识别.实验结果表明,相对于单一的特征识别方法,基于LBP_深度数据和Fisherface特征融合的方法更能提高三维人脸识别效率.

In order to improve the efficiency of 3D face recognition,a 3D face recognition method based on Fisherface and LBP （local binary pattern）was put forward.The face depth data was firstly extracted,then the feature of 3 D face was extracted by combining the depth data with LBP,finally the Fisherface method was used for identification.The experimental results showed that comparing with single recognition method, the efficiency of 3 D face recognition increased using Fisherface method based on LBP_depth data.