3D face recognition algorithm based on detecting reliable components  

作　　者：Huang Wenjun Zhou Xuebing Niu Xiamu 

机构地区：[1]Harbin Institute of Technology Shenzhen Graduate School, Room 304, Building No. 3, HIT Campus, Shenzhen 518055, P. R. China [2]Fraunhofer IGD, Fraunhoferstr. 5, Darmstadt 64283, Germany

出　　处：《仪器仪表学报》2007年第5期769-773,共5页Chinese Journal of Scientific Instrument

基　　金：Supported by the National Natural Science Foundation of China(60671064);the Foundation for the Author of National Excellent Doctoral Dissertation of China(FANEDD-200238);the Foundation for the Excellent Youth of Heilongjiang Province;the Program for New Century Excellent Talents in University(NCET-04-0330)

摘　　要：Fisherfaces algorithm is a popular method for face recognition.However,there exist some unstable com- ponents that degrade recognition performance.In this paper,we propose a method based on detecting reliable com- ponents to overcome the problem and introduce it to 3D face recognition.The reliable components are detected within the binary feature vector,which is generated from the Fisherfaces feature vector based on statistical properties,and is used for 3D face recognition as the final feature vector.Experimental results show that the reliable components fea- ture vector is much more effective than the Fisherfaces feature vector for face recognition.Fisherfaces algorithm is a popular method for face recognition. However, there exist some unstable components that degrade recognition performance. In this paper, we propose a method based on detecting reliable components to overcome the problem and introduce it to 3D face recognition. The reliable components are detected within the binary feature vector, which is generated from the Fisherfaces feature vector based on statistical properties, and is used for 3D face recognition as the final feature vector. Experimental results show that the reliable components feature vector is much more effective than the Fisherfaces feature vector for face recognition.

关 键 词：3D人脸识别 算法 检测 可靠度 统计特性 Fisherfaces 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]