Head pose estimation method based on pose manifold and tensor decomposition  

作　　者：Wei Wei Yanning Zhang Chunna Tian 

机构地区：[1]Department of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an 710072, P. R. China [2]School of Electronic Engineering, Xidian University, Xi'an 710071, R R. China

出　　处：《Journal of Systems Engineering and Electronics》2010年第5期907-913,共7页系统工程与电子技术（英文版）

基　　金：supported by National Natural Science Foundation of China (60903126;60872145);Doctoral Fund of Ministry of Education of China (20090203120011);Basic Science Research Fund in XidianUniversity (72105470)

摘　　要：Pose manifold and tensor decomposition are used to represent the nonlinear changes of multi-view faces for pose estimation,which cannot be well handled by principal component analysis or multilinear analysis methods.A pose manifold generation method is introduced to describe the nonlinearity in pose subspace.And a nonlinear kernel based method is used to build a smooth mapping from the low dimensional pose subspace to the high dimensional face image space.Then the tensor decomposition is applied to the nonlinear mapping coefficients to build an accurate multi-pose face model for pose estimation.More importantly,this paper gives a proper distance measurement on the pose manifold space for the nonlinear mapping and pose estimation.Experiments on the identity unseen face images show that the proposed method increases pose estimation rates by 13.8% and 10.9% against principal component analysis and multilinear analysis based methods respectively.Thus,the proposed method can be used to estimate a wide range of head poses.Pose manifold and tensor decomposition are used to represent the nonlinear changes of multi-view faces for pose estimation,which cannot be well handled by principal component analysis or multilinear analysis methods.A pose manifold generation method is introduced to describe the nonlinearity in pose subspace.And a nonlinear kernel based method is used to build a smooth mapping from the low dimensional pose subspace to the high dimensional face image space.Then the tensor decomposition is applied to the nonlinear mapping coefficients to build an accurate multi-pose face model for pose estimation.More importantly,this paper gives a proper distance measurement on the pose manifold space for the nonlinear mapping and pose estimation.Experiments on the identity unseen face images show that the proposed method increases pose estimation rates by 13.8% and 10.9% against principal component analysis and multilinear analysis based methods respectively.Thus,the proposed method can be used to estimate a wide range of head poses.

关 键 词：head pose estimation principal component analysis multilinear algebra manifold analysis. 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] V448.22[自动化与计算机技术—计算机科学与技术]