Face Recognition Using Depth Images Base Convolutional Neural Network

被引：0
|
作者：
Chen, Juxiang [1 ]
Zhang, Zhihao [1 ]
Yao, Liansheng [1 ]
Li, Bo [1 ]
Chen, Tong [1 ]
机构：
[1] SouthWest Univ, Chongqing Key Lab Nonlinear Circuits & Intelligen, Chongqing, Peoples R China
来源：
PROCEEDING OF THE 2019 INTERNATIONAL CONFERENCE ON COMPUTER, INFORMATION AND TELECOMMUNICATION SYSTEMS (IEEE CITS 2019) | 2019年
基金：
中国国家自然科学基金;
关键词：
face recognition; depth image; convolution neural network; deep learning;
D O I：
10.1109/cits.2019.8862099
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Face recognition based on depth images is widely studied due to its advantages of 3 dimensional information and environment illumination insensitivity. The traditional recognition methods in this field mainly focus on hand-crafted feature design, which cannot achieve satisfactory result. In addition, there is no fixed face feature extraction method. To achieve a better face recognition performance on depth images, this paper proposes a method based on Convolutional Neural Networks(CNN). The experiment performed on database IIITD Kinect suggests that the proposed CNN architecture has better recognition performance than some traditional manual feature extraction methods, such as HOG and LBP.
引用
收藏
页码：187 / 190
页数：4
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