CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Bayesian Learning for Neural Networks
Bayesian Learning for Neural Networks
Motion capture assisted animation: texturing and synthesis
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
A sketching interface for articulated figure animation
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Avatar-augmented online conversation
Avatar-augmented online conversation
Synthesizing physically realistic human motion in low-dimensional, behavior-specific spaces
ACM SIGGRAPH 2004 Papers
Style-based inverse kinematics
ACM SIGGRAPH 2004 Papers
Priors for People Tracking from Small Training Sets
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Virtually enhancing the perception of user actions
Proceedings of the 2005 international conference on Augmented tele-existence
Impact of Dynamics on Subspace Embedding and Tracking of Sequences
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
3D People Tracking with Gaussian Process Dynamical Models
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Vision-based human motion analysis: An overview
Computer Vision and Image Understanding
Gaussian Process Dynamical Models for Human Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctiveness in multimodal behaviors
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Region-Based vs. Edge-Based Registration for 3D Motion Capture by Real Time Monoscopic Vision
MIRAGE '09 Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques
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
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A challenge for 3D motion capture by monocular vision is 3D-2D projection ambiguities that may bring incorrect poses during tracking. In this paper, we propose improving 3D motion capture by learning human gesture models from a library of gestures with variants. This library has been created with virtual human animations. Gestures are described as Gaussian Process Dynamic Models (GPDM) and are used as constraints for motion tracking. Given the raw input poses from the tracker, the gesture model helps to correct ambiguous poses. The benefit of the proposed method is demonstrated with results.