Paper Info
Title
Pose-invariant face recognition using deformation analysis
Abstract
Over the last decade or so, face recognition has become a popular area of research in computer vision and one of the most successful applications of image analysis and understanding. In addition, recognition of faces under varied poses has been a challenging area of research due to the complexity of pose dispersion in feature space. This paper presents a novel and robust pose-invariant face recognition method. In this approach, first, the facial region is detected using the TSL color model. The direction of face or pose is estimated using facial features and the estimated pose vector is decomposed into X-Y-Z axes. Second, the input face is mapped by a deformable template using these vectors and the 3D CANDIDE face model. Finally, the mapped face is transformed to the frontal face which appropriates for face recognition by the estimated pose vector. Through the experiments, we come to validate the application of face detection model and the method for estimating facial poses. Moreover, the tests show that recognition rate is greatly boosted through the normalization of the poses.
Year
DOI
Venue
2005
10.1007/11565123_53
BVAI
Keywords
Field
DocType
pose-invariant face recognition,face detection model,face recognition,deformation analysis,robust pose-invariant face recognition,input face,candide face model,recognition rate,mapped face,frontal face,facial feature,tsl color model,face detection,image analysis,color model,feature space
Facial recognition system,Computer vision,Feature vector,Face hallucination,Normalization (statistics),Three-dimensional face recognition,Object-class detection,Computer science,Image processing,Artificial intelligence,Face detection
Conference
Volume
ISSN
ISBN
3704
0302-9743
3-540-29282-9
Citations 
PageRank 
References 
0
0.34
7
Authors
5
Name
Order
Citations
PageRank
Taeg-Keun Whangbo1256.66
Jae-Young Choi2783110.19
Murlikrishna Viswanathan3216.30
Nak-bin Kim401.01
Young-gyu Yang501.35