Active shape models—their training and application
Computer Vision and Image Understanding
Visual learning and recognition of 3-D objects from appearance
International Journal of Computer Vision
Mapping a manifold of perceptual observations
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
A Multilinear Singular Value Decomposition
SIAM Journal on Matrix Analysis and Applications
On the Best Rank-1 and Rank-(R1,R2,. . .,RN) Approximation of Higher-Order Tensors
SIAM Journal on Matrix Analysis and Applications
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Automatic Detection and Tracking of Human Motion with a View-Based Representation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Estimating Human Body Configurations Using Shape Context Matching
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Specialized mappings and the estimation of human body pose from a single image
HUMO '00 Proceedings of the Workshop on Human Motion (HUMO'00)
Nonlinear manifold learning for visual speech recognition
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Human Motion Signatures: Analysis, Synthesis, Recognition
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Fast Pose Estimation with Parameter-Sensitive Hashing
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Generative modeling for continuous non-linearly embedded visual inference
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Separating Style and Content with Bilinear Models
Neural Computation
Journal of Cognitive Neuroscience
Inferring 3D body pose from silhouettes using activity manifold learning
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
3D human pose from silhouettes by relevance vector regression
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Locating nose-tips and estimating head poses in images by tensorposes
IEEE Transactions on Circuits and Systems for Video Technology
Coupled Visual and Kinematic Manifold Models for Tracking
International Journal of Computer Vision
View and style-independent action manifolds for human activity recognition
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part VI
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If we consider the appearance of human motion such as gait, facial expression and gesturing, most of such activities result in nonlinear manifolds in the image space. Although the intrinsic body configuration manifolds might be very low in dimensionality, the resulting appearance manifold is challenging to model given various aspects that affects the appearance such as the view point, the person shape and appearance, etc. In this paper we learn decomposable generative models that explicitly decompose the intrinsic body configuration as a function of time from other conceptually orthogonal aspects that affects the appearance such as the view point, the person performing the action, etc. The frameworks is based on learning nonlinear mappings from a conceptual representation of the motion manifold that is homeomorphic to the actual manifold and decompose other sources of variation in the mapping coefficient space.