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Multi-pose facial correction based on Gaussian process with combined kernel function
Author(s): Shuyan Shi; Ruirui Ji; Fan Zhang
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Paper Abstract

In order to improve the recognition rate of various postures, this paper proposes a method of facial correction based on Gaussian Process which build a nonlinear regression model between the front and the side face with combined kernel function. The face images with horizontal angle from -45° to +45° can be properly corrected to front faces. Finally, Support Vector Machine is employed for face recognition. Experiments on CAS PEAL R1 face database show that Gaussian process can weaken the influence of pose changes and improve the accuracy of face recognition to certain extent.

Paper Details

Date Published: 10 April 2018
PDF: 8 pages
Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106150X (10 April 2018); doi: 10.1117/12.2303386
Show Author Affiliations
Shuyan Shi, Xi'an Univ. of Technology (China)
Ruirui Ji, Xi'an Univ. of Technology (China)
Fan Zhang, Xi'an Univ. of Technology (China)


Published in SPIE Proceedings Vol. 10615:
Ninth International Conference on Graphic and Image Processing (ICGIP 2017)
Hui Yu; Junyu Dong, Editor(s)

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