关节体变形从距离扫描数据

Brett Allen, B. Curless, Zoran Popovic
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引用次数: 386

摘要

本文提出了一种基于实例的计算骨骼驱动体变形的方法。我们的示例数据包括各种姿势的人体范围扫描。利用距离扫描期间捕获的标记,我们构建了运动学骨架并识别每次扫描的姿态。然后,我们使用可能的细分表面模板构建所有扫描的相互一致的参数化。细节变形表示为该表面的位移,并且在位移图中平滑地填充孔。最后,我们在姿态空间中使用k近邻插值来组合距离扫描。我们展示了具有可控姿态、运动学和底层表面形状的人体上半身的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Articulated body deformation from range scan data
This paper presents an example-based method for calculating skeleton-driven body deformations. Our example data consists of range scans of a human body in a variety of poses. Using markers captured during range scanning, we construct a kinematic skeleton and identify the pose of each scan. We then construct a mutually consistent parameterization of all the scans using a posable subdivision surface template. The detail deformations are represented as displacements from this surface, and holes are filled smoothly within the displacement maps. Finally, we combine the range scans using k-nearest neighbor interpolation in pose space. We demonstrate results for a human upper body with controllable pose, kinematics, and underlying surface shape.
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