From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Image Object Recognition using Mixture Densities
Journal of Mathematical Imaging and Vision
Principal Manifolds and Probabilistic Subspaces for Visual Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition from Long-Term Observations
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Kernel Eigenfaces vs. Kernel Fisherfaces: Face Recognition Using Kernel Methods
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Growing Gaussian Mixture Models for Pose Invariant Face Recognition
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Face Recognition Based on Fitting a 3D Morphable Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Real-Time Face Detection
International Journal of Computer Vision
Acquiring Linear Subspaces for Face Recognition under Variable Lighting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition with Image Sets Using Manifold Density Divergence
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Identifying Individuals in Video by Combining "Generative" and Discriminative Head Models
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
IEEE Transactions on Pattern Analysis and Machine Intelligence
Boosted manifold principal angles for image set-based recognition
Pattern Recognition
Combining appearance and motion for face and gender recognition from videos
Pattern Recognition
An information-theoretic approach to face recognition from face motion manifolds
Image and Vision Computing
Video-based face recognition using probabilistic appearance manifolds
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Face recognition from video using the generic shape-illumination manifold
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
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As a problem of high practical appeal but many outstanding challenges, computer-based face recognition remains a topic of extensive research attention. In this paper we are specifically interested in the task of identifying a person using multiple images both in training and as a query. Thus, a novel method is proposed which advances the state-of-the-art in set-based face recognition. The introduced approach is based on a previously described invariant in the form of generic shape-illumination effects. The contributions include (i) an analysis of the computational demands of the original method and a demonstration of its practical limitations, (ii) a novel representation of personal appearance in the form of linked mixture models in image and pose-signature spaces, and (iii) an efficient (in terms of storage needs and matching time) manifold re-illumination algorithm based on the aforementioned representation. An evaluation and comparison of the proposed method with the original generic shape-illumination algorithm shows that comparably high recognition rates are achieved on a large data set (1.5% error on 700 face sets containing 100 individuals and extreme illumination variation) with a dramatic improvement in matching speed (over 700 times for sets containing 1600 faces) and storage requirements (independent of the number of training images). Theoretical and empirical findings of the present work are used to identify and discuss avenues for future research.