Panoramic Face Recognition
Normally, modeling 3D face is an effective way for pose-invariant recognition, yet its expensive computation significantly discourages potential applications. In this paper, a simple and fully automatic panoramic image-based pose-invariant face recognition method is proposed to present excellent accuracy with low complexity. In this paper, a face shape model with local morphing treatment is first constructed and considered as the alignment standard to deal with all of the possible geometric distortion problems. During the recognition phase, a proposed systematically designed algorithm with morphing and the selection function are both utilized to significantly ease the negative effects of various poses within ±45° in yaw and ±22.5° in pitch. As demonstrated in experimental results, a similar accuracy as that of the 3D start-of-the-arts is achieved with much less computational complexity.