A multiresolution spline with application to image mosaics
ACM Transactions on Graphics (TOG)
Active shape models—their training and application
Computer Vision and Image Understanding
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
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
The CMU Pose, Illumination, and Expression Database
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Real-Time Face Detection
International Journal of Computer Vision
Active Appearance Models Revisited
International Journal of Computer Vision
Face Recognition Based on Frontal Views Generated from Non-Frontal Images
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
On the Euclidean Distance of Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image deformation using moving least squares
ACM SIGGRAPH 2006 Papers
Rank-one Projections with Adaptive Margins for Face Recognition
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Pattern Recognition, Third Edition
Pattern Recognition, Third Edition
Active Shape Models with Invariant Optimal Features: Application to Facial Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gait recognition for human identification based on ICA and fuzzy SVM through multiple views fusion
Pattern Recognition Letters
Enhancing Bilinear Subspace Learning by Element Rearrangement
IEEE Transactions on Pattern Analysis and Machine Intelligence
Semi-supervised bilinear subspace learning
IEEE Transactions on Image Processing
A doubly weighted approach for appearance-based subspace learning methods
IEEE Transactions on Information Forensics and Security
Regularized locality preserving projections and its extensions for face recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
Flexible manifold embedding: a framework for semi-supervised and unsupervised dimension reduction
IEEE Transactions on Image Processing
Bayesian tangent shape model: Estimating shape and pose parameters via bayesian inference
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Toward Pose-Invariant 2-D Face Recognition Through Point Distribution Models and Facial Symmetry
IEEE Transactions on Information Forensics and Security - Part 1
A Mosaicing Scheme for Pose-Invariant Face Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Locally Linear Regression for Pose-Invariant Face Recognition
IEEE Transactions on Image Processing
Face Recognition Using Spatially Constrained Earth Mover's Distance
IEEE Transactions on Image Processing
Face illumination compensation dictionary
Neurocomputing
Sparse Representation Shape Models
Journal of Mathematical Imaging and Vision
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A multi-to-one frontal view face synthesizing strategy, and how it could be utilized to improve traditional face recognition algorithms on pose variant problems, is introduced in this paper. The word multi-to-one means more than one input source images and one output synthetic image, and this is an information selection procedure. Through picking up the gray intensity most similar with that of frontal view face from multiple non-frontal input images, proposed algorithm tries to simulate real natural pose variance of human face. The similarity is evaluated according to the magnitude of non-rigid bending deformation involved during synthesizing, the underlying observation of which is, the more the bending deformation are utilized, the less natural the synthesized image looks like. The specific approach is realized based on Moving Least Squares (MLS). Besides synthesizing frontal faces, our Minimum Bending Synthesizing (MBS) strategy could also be utilized to unify the poses of both gallery and probe images, and hence effectively reduce the influence of variant pose to 2D face recognition. From experiments on the CMU PIE and FERET databases, it could be observed that the frontal view faces synthesized by MBS could effectively approximate the real ground truth frontal faces, and MBS could greatly improve the performance of classic face recognition algorithms, PCA and LDA, on pose variant problems. Apart from specific algorithms, the idea of synthesizing frontal face according to more than one input images, is much valuable as well.