Motion Capture Analysis and Reconstruction Using Spatial Keyframes
Motion Capture Analysis and Reconstruction Using Spatial Keyframes
复制标题
使用空间关键帧进行运动捕捉分析和重建
DOI：
10.1007/978-3-030-41590-7_3
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Claudio Esperança
中科院分区：
文献类型：
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作者：
B. F. Costa;Claudio Esperança
运动捕捉是为基于骨骼的模型创建逼真动画的首选技术。然而，捕获会话是昂贵的，并且产生的运动很难分析后修和重用。在本文中，我们提出了几个工具来分析和重建运动使用空间关键帧的概念，由Igarashi等人理想化。捕获的动作由平面上的曲线表示，通过多维投影获得，允许动画师将平面上的区域与姿态空间中的区域相关联，以便定位和收集具有代表性的姿态。通过实验测量不同的多维投影和插值算法的误差行为，研究了代表性姿态的重构问题。特别地，我们引入了一种新的多维投影优化，使重建误差最小化。这些想法在一个交互式应用程序中得到展示，该应用程序可以在线公开访问。
Motion capturing is the preferred technique to create realistic animations for skeleton-based models. Capture sessions, however, are costly and the resulting motions are hard to analyze for posterior modification and reuse. In this paper we propose several tools to analyze and reconstruct motions using the concept ofspatial keyframes, idealized by Igarashi et al. [19]. Captured motions are represented by curves on the plane obtained by multidimensional projection, allowing the animator to associate regions on that plane with regions in pose space so that representative poses can be located and harvested. The problem of reconstruction from representative poses is also investigated by conducting experiments that measure the error behavior with respect to different multidimensional projection and interpolation algorithms. In particular, we introduce a novel multidimensional projection optimization that minimizes reconstruction errors. These ideas are showcased in an interactive application that can be publicly accessed online.