基于协作补丁的三维表面跟踪

M. Klaudiny, A. Hilton
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引用次数: 12

摘要

本文提出了一种新颖的密集运动捕捉技术,该技术从动态对象的几个校准和同步视频序列中创建一个时间一致的网格序列。采用基于用户指定参考网格拓扑结构的表面贴片模型随时间跟踪对象的表面。使用新颖的协作最小化方法对表面斑块进行多视图3D匹配,提供初始运动估计,该估计对大而快速的非刚性形状变化具有鲁棒性。拉普拉斯变形随后使用加权顶点位移作为软约束来规范整个网格的运动。在每帧独立重建的未配准表面几何形状被合并为形状,以提高跟踪质量。该方法在一个具有挑战性的面部动作捕捉场景中进行了评估。结果显示准确跟踪快速,复杂的表达在长序列不使用标记或模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cooperative patch-based 3D surface tracking
This paper presents a novel dense motion capture technique which creates a temporally consistent mesh sequence from several calibrated and synchronised video sequences of a dynamic object. A surface patch model based on the topology of a user-specified reference mesh is employed to track the surface of the object over time. Multi-view 3D matching of surface patches using a novel cooperative minimisation approach provides initial motion estimates which are robust to large, rapid non-rigid changes of shape. A Laplacian deformation subsequently regularises the motion of the whole mesh using the weighted vertex displacements as soft constraints. An unregistered surface geometry independently reconstructed at each frame is incorporated as a shape prior to improve the quality of tracking. The method is evaluated in a challenging scenario of facial performance capture. Results demonstrate accurate tracking of fast, complex expressions over long sequences without use of markers or a pattern.
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