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Motion Parameterization with Inverse Blending

机译:反向融合运动参数化

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Motion blending is a popular motion synthesis technique which interpolates similar motion examples according to blending weighs parameterizing high-level characteristics of interest. We present in this paper an optimization framework for determining blending weights able to produce motions precisely satisfying multiple given spatial constraints. Our proposed method is simpler than previous approaches, and yet it can quickly achieve locally optimal solutions without pre-processing of basis functions. The effectiveness of our method is demonstrated in solving two classes of problems: 1) we show the precise control of end-effectors during the execution of diverse upper-body actions, and 2) we also address the problem of synthesizing walking animations with precise feet placements, demonstrating the ability to simultaneously meet multiple constraints and at different frames. Our several experimental results demonstrate that the proposed optimization approach is simple to implement and effectively achieves realistic results with precise motion control.
机译:运动融合是一种流行的运动合成技术,根据融合权重参数化感兴趣的高级特性,可以对相似的运动示例进行插值。我们在本文中提出了一种用于确定混合权重的优化框架,该混合权重能够产生精确地满足多个给定空间约束的运动。我们提出的方法比以前的方法更简单,但是它可以快速实现局部最优解,而无需预处理基础函数。我们的方法的有效性在解决两类问题中得到了证明:1)我们在执行各种上半身动作的过程中展示了对末端执行器的精确控制,并且2)我们还解决了用精确的脚合成步行动画的问题展示位置,展示了在不同框架下同时满足多个约束的能力。我们的几个实验结果表明,所提出的优化方法易于实现,并通过精确的运动控制有效地实现了逼真的结果。

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