用于动态序列合成的运动纹理模型

Motion Texture for Dynamic Sequence Synthesis

提出了一种新的用于动态序列合成的分层统计模型———运动纹理模型 .该模型使用统计方法自动分析动态序列 ,可以合成与原始样本数据统计特性相同的新的动态序列 .运动纹理模型是一个两层模型 .其中包含的两层分别为基元层和基元分布层 .模型中用线性动态系统来表示单个基元 .而对基元的统计分布则由相关转移矩阵来描述 .该文详细地讨论了如何通过最大似然准则来学习运动纹理模型的方法 ,并描述了如何用运动纹理模型自动合成动态序列的过程 .该文通过使用运动纹理模型合成舞蹈动作和视频序列的一些实验验证了该模型的有效性 .

We describe a novel model, called motion texture, for synthesizing complex dynamic sequences that are statistically similar to the original sample data. We define motion texture as a set of motion textons and their distribution, which characterize the stochastic and dynamic nature of the sample data. Specifically, a motion texton is modeled by a linear dynamic system (LDS) while the texton distribution is represented by a transition matrix indicating how likely each texton is switched to another. We design a maximum likelihood algorithm to learn the motion textons and their relationship. The learnt motion texture can then be used to generate new animations automatically. Our approach is demonstrated by many synthesized sequences of visually compelling dance motion and video sequences.