Comic character animation using Bayesian estimation

Yun Feng Chou*, Zen-Chung Shih

*此作品的通信作者

研究成果: Article同行評審

摘要

The motion of comic characters includes different types of movements, such as walking or running. In a comic, a movement may be described by a series of non-continuous poses in a sequence of contiguous frames. Each pose exists in a frame. We synthesize an animation according to still comic frames. In this paper, we propose a model to analyze time series of a character's motion using the non-parametric Bayesian approach. Then we can automatically generate a sequence of motions by using the estimated time series. Experimental results show that the built time series model best matches the given frames. Furthermore, unnatural distortions of the results are minimized.

原文English
頁(從 - 到)457-470
頁數14
期刊Computer Animation and Virtual Worlds
22
發行號5
DOIs
出版狀態Published - 1 9月 2011

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