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- W2017026595 abstract "Abstract Synthesizing the movements of a responsive virtual character in the event of unexpected perturbations has proven a difficult challenge. To solve this problem, we devise a fully automatic method that learns a nonlinear probabilistic model of dynamic responses from very few perturbed walking sequences. This model is able to synthesize responses and recovery motions under new perturbations different from those in the training examples. When perturbations occur, we propose a physics‐based method that initiates motion transitions to the most probable response example based on the dynamic states of the character. Our algorithm can be applied to any motion sequences without the need for preprocessing such as segmentation or alignment. The results show that three perturbed motion clips can sufficiently generate a variety of realistic responses, and 14 clips can create a responsive virtual character that reacts realistically to external forces in different directions applied on different body parts at different moments in time." @default.
- W2017026595 created "2016-06-24" @default.
- W2017026595 creator A5061025203 @default.
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- W2017026595 date "2010-05-01" @default.
- W2017026595 modified "2023-10-18" @default.
- W2017026595 title "Synthesis of Responsive Motion Using a Dynamic Model" @default.
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- W2017026595 doi "https://doi.org/10.1111/j.1467-8659.2009.01625.x" @default.
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