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Skilled dancers are often characterized by a unique style of movement that distinguishes them from others, suggesting that a computational representation of these audio-dependent movement patterns may be possible. For this project, we look at a very small slice of the bigger picture by using motion graphs to generate novel motions in the style of a target subject independently of audio.
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