Tracking, Analysis, and Recognition of Human Gestures in Video
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Video-guided motion synthesis using example motions
ACM Transactions on Graphics (TOG)
Temporal motion models for monocular and multiview 3D human body tracking
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Gait analysis for human identification through manifold learning and HMM
Pattern Recognition
Monocular 3D tracking of articulated human motion in silhouette and pose manifolds
Journal on Image and Video Processing - Anthropocentric Video Analysis: Tools and Applications
Fast nonparametric belief propagation for real-time stereo articulated body tracking
Computer Vision and Image Understanding
Appearance modeling using a geometric transform
IEEE Transactions on Image Processing
3D Human Motion Tracking with a Coordinated Mixture of Factor Analyzers
International Journal of Computer Vision
Coupled Visual and Kinematic Manifold Models for Tracking
International Journal of Computer Vision
Visual tracking of independently moving body and arms
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Modeling human locomotion with topologically constrained latent variable models
Proceedings of the 2nd conference on Human motion: understanding, modeling, capture and animation
Tracking human pose with multiple activity models
Pattern Recognition
Large margin cost-sensitive learning of conditional random fields
Pattern Recognition
Dual gait generative models for human motion estimation from a single camera
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on gait analysis
Latent gaussian mixture regression for human pose estimation
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Sequence classification via large margin hidden Markov models
Data Mining and Knowledge Discovery
Dynamic hand shape manifold embedding and tracking from depth maps
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
Conditional ordinal random fields for structured ordinal-valued label prediction
Data Mining and Knowledge Discovery
| Hi-index | 0.00 |
A learning based framework is proposed for estimating human body pose from a single image. Given a differentiable function that maps from pose space to image feature space, the goal is to invert the process: estimate the pose given only image features. The inversion is an ill-posed problem as the inverse mapping is a one to many process, hence multiple solutions exist. It is desirable to restrict the solution space to a smaller subset of feasible solutions. The space of feasible solutions may not admit a closed form description. The proposed framework seeks to learn an approximation over such a space. Using Gaussian Process Latent Variable Modelling. The scaled conjugate gradient method is used to find the best matching pose in the learned space. The formulation allows easy incorporation of various constraints for more accurate pose estimation. The performance of the proposed approach is evaluated in the task of upper-body pose estimation from silhouettes and compared with the Specialized Mapping Architecture. The proposed approach performs better than the latter approach in terms of estimation accuracy with synthetic data and qualitatively better results with real video of humans performing gestures.