10 April 2018 Multi-pose facial correction based on Gaussian process with combined kernel function
Author Affiliations +
Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 106150X (2018) https://doi.org/10.1117/12.2303386
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China
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.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shuyan Shi, Ruirui Ji, Fan Zhang, "Multi-pose facial correction based on Gaussian process with combined kernel function", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106150X (10 April 2018); doi: 10.1117/12.2303386; https://doi.org/10.1117/12.2303386
PROCEEDINGS
8 PAGES


SHARE
RELATED CONTENT

A review on face recognition techniques
Proceedings of SPIE (January 28 2013)
A higher-order-statistics-based approach to face detection
Proceedings of SPIE (February 08 2005)
Sampling design for face recognition
Proceedings of SPIE (April 17 2006)

Back to Top