A Coherent Locomotion Engine Extrapolating Beyond Experimental Data
نویسندگان
چکیده
The generation of motion, and specifically locomotion, encompasses widely accepted techniques like blending or scattered data interpolation. To ensure a real-time simulation, each frame of the resulting animation is computed only when it has to be displayed, even if user parameters have not been modified. Thus, existing methods cannot reduce their computation cost in case of complex animation framework. Additionally, as the motion is computed frame by frame, no motion prediction can be performed. In this paper, we propose an on-line reactive method that generates the whole new locomotion sequence only at each user parameters update. Using experimental data of locomotion capture in a coherent framework, the resulting engine is able to animate on the fly humanlike characters of any size and proportions, through the control of high-level parameters. Moreover, we improve existing techniques for a better and quantitative extrapolation of physical parameters of different locomotion types.
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تاریخ انتشار 2004