Using Discriminant Eigenfeatures for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Based on Fitting a 3D Morphable Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
The CMU Pose, Illumination, and Expression Database
IEEE Transactions on Pattern Analysis and Machine Intelligence
Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
Appearance-Based Face Recognition and Light-Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
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
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Separating Style and Content with Bilinear Models
Neural Computation
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Journal of Cognitive Neuroscience
Tied Factor Analysis for Face Recognition across Large Pose Differences
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Viewpoint Invariant, Sparsely Registered, Patch Based, Face Verifier
International Journal of Computer Vision
Face recognition across pose: A review
Pattern Recognition
Efficient Sparse Kernel Feature Extraction Based on Partial Least Squares
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Stereo Matching with General Epipolar Geometry for 2D Face Recognition across Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image and Vision Computing
A robust and scalable approach to face identification
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part VI
Curse of mis-alignment in face recognition: problem and a novel mis-alignment learning solution
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Face recognition under varying lighting conditions using self quotient image
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Cross-pose face recognition based on partial least squares
Pattern Recognition Letters
Unconstrained Pose-Invariant Face Recognition Using 3D Generic Elastic Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Probabilistic Models for Inference about Identity
IEEE Transactions on Pattern Analysis and Machine Intelligence
Overview and recent advances in partial least squares
SLSFS'05 Proceedings of the 2005 international conference on Subspace, Latent Structure and Feature Selection
Bypassing synthesis: PLS for face recognition with pose, low-resolution and sketch
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Wide-baseline stereo for face recognition with large pose variation
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
An associate-predict model for face recognition
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Locally Linear Regression for Pose-Invariant Face Recognition
IEEE Transactions on Image Processing
Coupled Bias–Variance Tradeoff for Cross-Pose Face Recognition
IEEE Transactions on Image Processing
Fully automatic pose-invariant face recognition via 3D pose normalization
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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We propose a novel pose-invariant face recognition approach which we call Discriminant Multiple Coupled Latent Subspace framework. It finds the sets of projection directions for different poses such that the projected images of the same subject in different poses are maximally correlated in the latent space. Discriminant analysis with artificially simulated pose errors in the latent space makes it robust to small pose errors caused due to a subject's incorrect pose estimation. We do a comparative analysis of three popular latent space learning approaches: Partial Least Squares (PLSs), Bilinear Model (BLM) and Canonical Correlational Analysis (CCA) in the proposed coupled latent subspace framework. We experimentally demonstrate that using more than two poses simultaneously with CCA results in better performance. We report state-of-the-art results for pose-invariant face recognition on CMU PIE and FERET and comparable results on MultiPIE when using only four fiducial points for alignment and intensity features.