Realistic Synthesis of Novel Human Movements from a Database of Motion Capture Examples
نویسندگان
چکیده
In this paper we present a system that can synthesise novel motion sequences from a database of motion capture examples. This is achieved through learning a statistical model from the captured data which enables realistic synthesis of new movements by sampling the original captured sequences. New movements are synthesised by specifying the start and end keyframes. The statistical model identifies segments of the original motion capture data to generate novel motion sequences between the keyframes. The advantage of this approach is that it combines the flexibility of keyframe animation with the realism of motion capture data.
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My research interests have revolved around creating realistic animated humans. Animated humans are important to a variety of applications, including: entertainment, where they appear as characters in games and as special effects in movies; training simulations, which are used by the military to prepare soldiers and by industry to instruct workers in using equipment; and visualization aids, such...
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