[1]ZHANG Yi,LIAO Qiaozhen,LUO Yuan.Head pose estimation fusing the second order HOG and CS-LBP[J].CAAI Transactions on Intelligent Systems,2015,10(5):741-746.[doi:10.11992/tis.201506019]
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Head pose estimation fusing the second order HOG and CS-LBP

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 10 Number of periods: 2015 5 Page number: 741-746 Column: 学术论文—机器感知与模式识别 Public date: 2015-10-25
Title:
Head pose estimation fusing the second order HOG and CS-LBP
Author(s):
ZHANG Yi1;  LIAO Qiaozhen1;  LUO Yuan2
1. College of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;
2. College of Photoelectric Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Keywords:
head pose estimation; histogram of the orientation gradient (HOG); center symmetric local binary pattern (CS-LBP); kernel principal component analysis (KPCA); support vector machine (SVM)
CLC:
TP391.4
DOI:
10.11992/tis.201506019
Abstract:
In order to improve head pose recognition rate under variable illumination, expression, and noise, etc., a novel pose feature, fusing the second order histogram of the orientation gradient (HOG) with the center symmetric local binary pattern (CS-LBP) feature, is proposed in order to estimate head pose in a single frame image. The contour information of the facial image is extracted by the second order HOG, deriving the facial contour feature. CS-LBP is used to extract local texture information. More effective facial features can be obtained by fusing contour feature extracted by the second order HOG and the texture feature extracted by CS-LBP. Kernel principal component analysis (KPCA) is used to nonlinearly project the fused pose feature into a higher dimensional kernel space so as to further select the primary feature. A support vector machine (SVM) classifier is used for pose estimation. Experiment results show that the proposed method is more accurate than the HOG method and the LBP method. This method has good robustness for variable illumination.
References:
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