
High quality human motion data is expensive, whether it comes from captured human motion, motion created by a talented animator, or motion developed by an experienced behavior designer. The goal of this project is to reduce the expense involved in creating new motion and altering existing motion in a realistic manner. One objective is to develop a real-time environment that allows an animator to interact with physically-based models. We are also developing techniques to allow users to incrementally create physically-based animations.
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Participants: Nancy Pollard, Jonathan Cummings, Carolyn Uy, Fareed Behmaram-Mosavat
Participants: Anthony Fang
Participants: Remco Chang

2D or 3D plots are not always the best way to visualize information about the physics of motion. This project is investigating techniques to assist a user in understanding motion from a physical point of view.
Participants: Moira Burke (U. of Oregon)
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We are exploring image-based techniques to allow large groups of characters to be viewed and controlled in real-time. As rendering algorithms become more complex, the rendering step may become the main bottleneck to achieving real-time animation of large scenes. If we can avoid re-rendering characters for a number of frames yet still represent the character's appearance and motion with an acceptable level of fidelity, then we can display and control larger scenes in real-time.
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Participants: Audrey Wong

Football coaches create and distribute playbooks for their teams at the start of every season. These playbooks represent a static image of each play. A computer representation of such a playbook has a large number of advantages, including the ability to view the evolution of a play over time, develop new plays on the fly, and present a view of the field from any player's point of view. We are creating a gesture-based implementation of an electronic playbook.
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Participants: Jeff Pickering
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