Face recognition based on pose-variant image synthesis and multi-level multi-feature fusion

Authors:
Congcong Li;Guangda Su;Yan Shang;Yingchun Li;Yan Xiang
Affiliations:
Electronic Engineering Department, Tsinghua University, Beijing, China;Electronic Engineering Department, Tsinghua University, Beijing, China;Electronic Engineering Department, Tsinghua University, Beijing, China;Electronic Engineering Department, Tsinghua University, Beijing, China;Electronic Engineering Department, Tsinghua University, Beijing, China
Venue:
AMFG'07 Proceedings of the 3rd international conference on Analysis and modeling of faces and gestures
Year:
2007

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Abstract

Pose variance remains a challenging problem for face recognition. In this paper, a scheme including image synthesis and recognition is proposed to improve the performance of automatic face recognition system. In the image synthesis part, a series of pose-variant images are produced based on three images respectively with front, left-profile, right-profile poses, and are added into the gallery in order to overcome the pose inconsistence between probes and images in the database. In the recognition part, a multi-level fusion method based on Gabor-combined features and gray-intensity features (GCGIF) is presented. Both amplitude features and phase features extracted through Gabor filters are utilized. Fusion is introduced in both the face representation level and the confidence level. Experiment results show that the integrated scheme achieve superior recognition performance.