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模板化的人体运动合成

DOI: 10.16383/j.aas.2015.c140457, PP. 758-771

Keywords: 运动合成,模板化,运动参数,语义特征

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Abstract:

?为解决现有运动合成方法中控制方式过于复杂的问题,提出一种模板化的运动合成模型,旨在降低运动合成技术的应用门槛.利用稀疏主成分分析(Sparseprincipalcomponentanalysis,SPCA)、Grouplasso和Exclusivegrouplasso对人体运动进行建模,使其对应的每一个低维参数只依赖于少数几个人体关节,构成人体运动的一个内在自由度(Degreeoffreedom,DOF),并具有直观语义;同时,每个关节被尽量少的低维参数所控制,以减少低维参数对彼此所控制的自由度的交叉影响.实验表明,通过直观地修改低维参数,就能够实时地控制每个参数对应的摆臂幅度、踢腿高度、跳跃距离等运动属性.这种"模板学习、模板定制"的两步方法,有效地降低了运动合成控制的复杂度,即便非专业人员也可以用其进行艺术创作.

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