Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparative Study of Coarse Head Pose Estimation
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
Think globally, fit locally: unsupervised learning of low dimensional manifolds
The Journal of Machine Learning Research
Head Pose Estimation using Fisher Manifold Learning
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
Facial Expression Decomposition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
A Probabilistic Framework for Joint Head Tracking and Pose Estimation
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Head Pose Estimation by Nonlinear Manifold Learning
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Face Recognition Using Laplacianfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Head Pose Estimation of Partially Occluded Faces
CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision
Graph Embedded Analysis for Head Pose Estimation
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Graph Embedding and Extensions: A General Framework for Dimensionality Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Cognitive Neuroscience
Supervised locally linear embedding
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Unsupervised learning of image manifolds by semidefinite programming
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Comparing different classifiers for automatic age estimation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Learning multiview face subspaces and facial pose estimation using independent component analysis
IEEE Transactions on Image Processing
Discriminative Locality Alignment
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
ICVS '09 Proceedings of the 7th International Conference on Computer Vision Systems: Computer Vision Systems
Uncorrelated discriminant simplex analysis for view-invariant gait signal computing
Pattern Recognition Letters
Optimal regularization parameter estimation for spectral regression discriminant analysis
IEEE Transactions on Circuits and Systems for Video Technology
A new representation method of head images for head pose estimation
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Head pose estimation based on manifold embedding and distance metric learning
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part I
Image and Vision Computing
Two-layer dual gait generative models for human motion estimation from a single camera
Image and Vision Computing
Parameterless Local Discriminant Embedding
Neural Processing Letters
Shape classification by manifold learning in multiple observation spaces
Information Sciences: an International Journal
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Precise 3-D head pose estimation plays a significant role in developing human-computer interfaces and practical face recognition systems. This task is challenging due to the particular appearance variations caused by pose changes for a certain subject. In this paper, the pose data space is considered as a union of submanifolds which characterize different subjects, instead of a single continuous manifold as conventionally regarded. A novel manifold embedding algorithm dually supervised by both identity and pose information, called snchronized submanifold embedding (SSE), is proposed for person-independent precise 3-D pose estimation, which means that the testing subject may not appear in the model training stage. First, the submanifold of a certain subject is approximated as a set of simplexes constructed using neighboring samples. Then, these simplexized submanifolds from different subjects are embedded by synchronizing the locally propagated poses within the simplexes and at the same time maximizing the intrasubmanifold variances. Finally, the pose of a new datum is estimated as the propagated pose of the nearest point within the simplex constructed by its nearest neighbors in the dimensionality reduced feature space. The experiments on the 3-D pose estimation database, CHIL data for CLEAR07 evaluation, and the extended application for age estimation on FG-NET aging database, demonstrate the superiority of SSE over conventional regression algorithms as well as unsupervised manifold learning algorithms.