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Near-optimal Character Animation with Continuous Control

We present a new approach to realtime character animation with interactive control. Given a corpus of motion capture data and a desired task, we automatically compute near-optimal controllers using a low-dimensional basis representation. We show that these controllers produce motion that fluidly responds to several dimensions of user control and environmental constraints in realtime. Our results indicate that very few basis functions are required to create high-fidelity character controllers which permit complex user navigation and obstacle-avoidance tasks

Keyframe Control of Smoke Simulations

We describe a method for controlling smoke simulations through user-specified keyframes. To achieve the desired behavior, a continuous quasi-Newton optimization solves for appropriate "wind" forces to be applied to the underlying velocity field throughout the simulation. The cornerstone of our approach is a method to efficiently compute exact derivatives through the steps of a fluid simulation. We formulate an objective function corresponding to how well a simulation matches the user's keyframes, and use the derivatives to solve for force parameters that minimize this function. For animations with several keyframes, we present a novel multipleshooting approach. By splitting large problems into smaller overlapping subproblems, we greatly speed up the optimization process while avoiding certain local minima