Title: Pose robust face recognition based on kernel regression in Bayesian framework

Authors: Ying Chen; Longyuan Zhang; Xiuxiao Guo

Addresses: Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi city, Jiangsu Province 214122, China ' Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi city, Jiangsu Province 214122, China ' Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi city, Jiangsu Province 214122, China

Abstract: To reduce the effect brought by variation of pose, a face recognition system is proposed, in which the correlation between two faces by probabilistic models is computed and the gallery is extended with profile faces generated by a regression-based method. Each face is divided into 3 × 3 regions, and by measuring the distance between the two corresponding regions the distributions of similarities are learned and Bayesian models are formed for each region. These probabilistic models are used to determine whether two faces belong to the same subject. Besides, the gallery is expanded with profile facial images. With this approach, the landmarks on non-frontal faces can be estimated from their frontal landmarks by the mappings learned offline via kernel rank reduced regression (KRRR). Then the profile images are achieved by piecewise affine warping from the corresponding frontal face. Experiments indicate the proposed method performed well, especially when the head rotation angle is large.

Keywords: face recognition; MRH; multi-region probabilistic histograms; Bayesian modelling; synthesis; virtual faces; KRRR; kernel reduced rank regression; pose; head rotation angle; piece affine warping; probabilistic modelling; profile images; facial images; biometrics; facial profiles.

DOI: 10.1504/IJCAT.2014.062366

International Journal of Computer Applications in Technology, 2014 Vol.49 No.3/4, pp.306 - 315

Published online: 02 Mar 2015 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article