3D Face Recognition Using Corresponding Point Direction Measure and Depth Local Features

摘要：

A new scheme for 3D face recognition is presented in this paper. Firstly, we use Iterative Closet Point (ICP) to align all 3D faces with the first 3D face. Secondly, we reduce noise, especially the noise which in front of the face, and remove the spikes. Then we detect the nose tip point. Once the nose tip is successfully found, we crop a region, which is defined by a sphere radius of 100 mm centered at the nose tip. Then we use the Corresponding Point Direction Measure (CPDM) to matching the 3D face with the gallery 3D faces and get the score. At the same time, we use the region to construct depth image, and get the Gabor feature, LBP feature, principle component of the depth image. Finally, we fuse the CPDM result, Gabor feature, LBP feature, and principle component of depth image to finish the recognition. This paper presents a new method for matching 3D face and a new scheme for 3D face recognition. Experiments demonstrated the efficiency and effectiveness of the new method.

关键词： Iterative Closet Point Corresponding Point Direction Measure Principle Component Analysis Gabor feature LBP

作者: Xueqiao Wang Qiuqi Ruan Yue Ming

作者单位: Institute of Information Science, Beijing Jiaotong University, Beijing 100044, P.R.China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 86-89

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）