减少标记布局的光学动作捕捉的手

Matthias Schröder, Jonathan Maycock, M. Botsch
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引用次数: 24

摘要

我们提出了一种自动生成减少标记布局的方法,用于基于标记的人类手部运动的光学运动捕捉。减少手上的标记数量对于确保生成的动作以自然的方式进行是很重要的,实际上,如果必须同时进行身体动作捕捉,减少标记集可能是一项技术要求。所采用的运动重建方法是基于子空间约束的逆运动学,它允许从稀疏输入数据中恢复真实的手部运动。我们的标记布局优化对运动学结构和重构方法中使用的手关节的子空间表示敏感,以便生成最优的稀疏标记配置,以解决约束逆运动学问题。我们提出了具体的质量标准,减少标记集,结合数值稳定性和几何可行性的结果布局。这些准则组合在一个目标函数中,该目标函数使用专门的表面约束粒子群优化方案最小化。我们的方法提供了一种基于手关节的子空间表示来确定减少标记布局的原则方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reduced marker layouts for optical motion capture of hands
We present a method for automatically generating reduced marker layouts for marker-based optical motion capture of human hand motions. Reducing the number of markers on the hand is important to ensure the generated motions are performed in a natural way and indeed a reduced marker set might be a technical requirement should simultaneous body motion capture also have to be carried out. The employed motion reconstruction method is based on subspace-constrained inverse kinematics, which allows for the recovery of realistic hand movements even from sparse input data. Our marker layout optimization is sensitive to the kinematic structure and the subspace representations of hand articulations utilized in the reconstruction method in order to generate sparse marker configurations that are optimal for solving the constrained inverse kinematics problem. We propose specific quality criteria for reduced marker sets that combine numerical stability with geometric feasibility of the resulting layout. These criteria are combined in an objective function that is minimized using a specialized surface-constrained particle swarm optimization scheme. Our method provides a principled way for determining reduced marker layouts based on subspace representations of hand articulations.
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