Pose Invariant Approach for Face Recognition at Distance

Eslam Mostafa¹, Asem Ali^{1, 2}, Naif Alajlan³, and Aly Farag¹

¹CVIP Lab, University of Louisville, Louisville, KY, USA
eslam.mostafa@louisville.edu
asem.ali@louisville.edu
aly.farag@louisville.edu
http://www.cvip.uofl.edu

²EE Department, Assiut University, Assiut, Egypt

³CIS Department, King Saud University, Riyadh, Saudi Arabia
najlan@KSU.EDU.SA

Abstract. We propose an automatic pose invariant approach for Face Recognition At a Distance (FRAD). Since face alignment is a crucial step in face recognition systems, we propose a novel facial features extraction model, which guides extended ASM to accurately align the face. Our main concern is to recognize human faces under uncontrolled environment at far distances accurately and fast. To achieve this goal, we perform an offline stage where 3D faces are reconstructed from stereo pair images. These 3D shapes are used to synthesize virtual 2D views in novel poses. To obtain good synthesized images from the 3D shape, we propose an accurate 3D reconstruction framework, which carefully handles illumination variance, occlusion, and the disparity discontinuity. The online phase is fast where a 2D image with unknown pose is matched with the closest virtual images in sampled poses. Experiments show that our approach outperforms the-state-of-the-art approaches.

LNCS 7577, p. 15 ff.

Full article in PDF | BibTeX

lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2012