吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (增刊1): 43-46.

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Pose estimation of varied human faces based on PCA method

SONG Huai-bo1, SHI Jian-qiang1,2   

  1. 1. College of Mechanical and Electric Engineering, Northwest A&F University, Yangling 712100, China;
    2. School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China
  • Received:2012-06-19 Published:2013-06-01

Abstract:

Pose estimation of different human faces is a key technology of varied human face recognitions which has not been well resolved yet.In order to get the mapping between face poses and feature spaces,an algorithm based on PCA was presented to realize the face pose estimations.Firstly,the subspaces and eigenvectors of different poses was built and selected by using PCA theory.Secondly,the Euclidean distance classifier was chosen to estimate the multi-poses of human faces.Lastly,the relationship between PCA's Variance contribution rates and pose estimation accuracy rates was investigated in detail.The algorithm was validated by means of experimental tests of human face pose database,which contains 23 kinds of poses and 630 samples in detail;experimental results show that the precision of this algorithm is above 84%.It also shows that the PCA based pose estimation method is feasible and valid for varied human face recognition.

Key words: face pose estimation, principal component analysis(PCA), pose subspace, variance contribution, eigenvectors

CLC Number: 

  • TP391.41

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