Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Face Recognition: Features Versus Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
View-Based Recognition of Faces in Man and Machine: Re-visiting Inter-extra-Ortho
BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Face Recognition Under Varying Pose
Face Recognition Under Varying Pose
Multiple Nose Region Matching for 3D Face Recognition under Varying Facial Expression
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using multi-instance enrollment to improve performance of 3D face recognition
Computer Vision and Image Understanding
Face recognition using principle components and linear discriminant analysis
ISPRA'09 Proceedings of the 8th WSEAS international conference on Signal processing, robotics and automation
Expression recognition in videos using a weighted component-based feature descriptor
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
Facial expression recognition from near-infrared videos
Image and Vision Computing
A survey of 3d face recognition methods
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
An effective method for detecting facial features and face in human-robot interaction
Information Sciences: an International Journal
Discriminant phase component for face recognition
Journal of Electrical and Computer Engineering
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We present a method for automatically learning a set of discriminatory facial components for face recognition. The algorithm performs an iterative growing of components starting with small initial components located around preselected points in the face. The direction of growing is determined by the gradient of the cross-validation error of the component classifiers. In experiments we analyze how the shape of the components and their discriminatory power changes across different individuals and views.