Authors: WonSeob Jang WonKyu Lee InKwon Lee Jehee Lee
Publish Date: 2007/12/20
Volume: 24, Issue: 4, Pages: 271-280
Abstract
We have synthesized new human body motions from existing motion data by dividing the body of an animated character into several parts such as upper and lower body and partitioning the motion of the character into corresponding partial motions By combining different partial motions we can generate new motion sequences We select the most naturallooking combinations by analyzing the similarity of partial motions using techniques such as motion segmentation dimensionality reduction and clustering These new combinations can dramatically increase the size of a motion database allowing more score in selecting motions to meet constraints such as collision avoidance We verify the naturalness and physical plausibility of the new motions using an SVM learning model and by analysis of static and dynamic balance
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