Physical Touch-Up of Human Motions
PG '03 Proceedings of the 11th Pacific Conference on Computer Graphics and Applications
Enriching a motion collection by transplanting limbs
SCA '04 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation
Interactive motion deformation with prioritized constraints
SCA '04 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation
Momentum-based parameterization of dynamic character motion
SCA '04 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation
A physically-based motion retargeting filter
ACM Transactions on Graphics (TOG)
Adaptation of performed ballistic motion
ACM Transactions on Graphics (TOG)
Interactive motion deformation with prioritized constraints
Graphical Models - Special issue on SCA 2004
Momentum-based parameterization of dynamic character motion
Graphical Models - Special issue on SCA 2004
History: The use of the kalman filter for human motion tracking in virtual reality
Presence: Teleoperators and Virtual Environments
Responsive action generation by physically-based motion retrieval and adaptation
MIG'10 Proceedings of the Third international conference on Motion in games
Dynamic control of captured motions to verify new constraints
GW'05 Proceedings of the 6th international conference on Gesture in Human-Computer Interaction and Simulation
Interactive editing of deformable simulations
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
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This paper presents a new method for editing an existing motion to satisfy a set of user-specified constraints, and in doing so guaranteeing the kinematic and dynamic soundness of the transformed motion. We cast the motion editing problem as a constrained state estimation problem based on the per-frame Kalman filter framework. To handle variouskinds of kinematic and dynamic constraints in a scalable fashion, we develop a new algorithm called spacetime sweeping, which sweeps through the frames with two consecutive filters. The unscented Kalman (UK) filter estimates an optimal pose for the current frame that conforms to the given constraints, and feeds the result to the least-squares (LS) filter. Then, the LS filter resolves the inter-frame inconsistencies introduced by the UK filter due to the independent handling of the position, velocity, and acceleration. The per-frame approach of the spacetime sweeping provides a surprising performance gain. It is remarkable that nowediting of motion that involves dynamic constraints such as dynamic balancing can be done interactively.