Title
Face recognition based on pose-variant image synthesis and multi-level multi-feature fusion
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.
Year
DOI
Venue
2007
10.1007/978-3-540-75690-3_20
AMFG
Keywords
Field
DocType
multi-level fusion method,confidence level,automatic face recognition system,recognition part,integrated scheme,face recognition,multi-level multi-feature fusion,face representation level,pose-variant image synthesis,image synthesis part,image synthesis,superior recognition performance,feature extraction
Computer vision,Facial recognition system,Feature fusion,Three-dimensional face recognition,Pattern recognition,Computer science,Face synthesis,Fusion,Image synthesis,Artificial intelligence
Conference
Volume
ISSN
ISBN
4778
0302-9743
3-540-75689-2
Citations 
PageRank 
References 
2
0.37
9
Authors
5
Name
Order
Citations
PageRank
Congcong Li124016.48
Guangda Su213320.68
Yan Shang3484.04
Yingchun Li451.50
Xiang Yan56617.39