Realistic Synthesis of Novel Human Movements from a Database of Motion Capture Examples

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.

• Type: Conference
• Year: 2000
• Where: HUMO
• Authors: L. M. Tanco, Adrian Hilton
• Keywords: Computer Animation, HUMO 2000, Motion Capture, Motion Capture Data, Motion Capture Examples