Face Recognition Based on Fitting a 3D Morphable Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Probabilistic recognition of human faces from video
Computer Vision and Image Understanding - Special issue on Face recognition
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
The CMU Pose, Illumination, and Expression Database
IEEE Transactions on Pattern Analysis and Machine Intelligence
Appearance-Based Face Recognition and Light-Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pose-Robust Face Recognition Using Geometry Assisted Probabilistic Modeling
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Journal of Cognitive Neuroscience
Accurate face models from uncalibrated and Ill-Lit video sequences
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
The CMU face in action (FIA) database
AMFG'05 Proceedings of the Second international conference on Analysis and Modelling of Faces and Gestures
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This paper proposes a novel face mosaicing approach to modeling human facial appearance and geometry in a unified framework. The human head geometry is approximated with a 3D ellipsoid model. Multi-view face images are back projected onto the surface of the ellipsoid, and the surface texture map is decomposed into an array of local patches, which are allowed to move locally in order to achieve better correspondences among multiple views. Finally the corresponding patches are trained to model facial appearance. And a deviation model obtained from patch movements is used to model the face geometry. Our approach is applied to pose robust face recognition. Using the CMU PIE database, we show experimentally that the proposed algorithm provides better performance than the baseline algorithms. We also extend our approach to video-based face recognition and test it on the Face In Action database.