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Global 3D Non-Rigid Registration of Deformable Objects Using a Single RGB-D Camera

机译:使用单个RGB-D摄像机对变形对象进行全局3D非刚性配准

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摘要

We present a novel global non-rigid registration method for dynamic 3D objects. Our method allows objects to undergo large non-rigid deformations and achieves high-quality results even with substantial pose change or camera motion between views. In addition, our method does not require a template prior and uses less raw data than tracking-based methods since only a sparse set of scans is needed. We simultaneously compute the deformations of all the scans by optimizing a global alignment problem to avoid the well-known loop closure problem and use an as-rigid-as-possible constraint to eliminate the shrinkage problem of the deformed shapes, especially near open boundaries of scans. To cope with large-scale problems, we design a coarse-to-fine multi-resolution scheme, which also avoids the optimization being trapped into local minima. The proposed method is evaluated on public datasets and real datasets captured by an RGB-D sensor. The experimental results demonstrate that the proposed method obtains better results than several state-of-the-art methods.
机译:我们为动态3D对象提出了一种新颖的全局非刚性注册方法。我们的方法允许对象经历较大的非刚性变形,即使在姿势之间发生重大变化或摄像机在视图之间移动时,也可以获得高质量的结果。此外,由于仅需要稀疏的扫描集,因此我们的方法不需要先验模板,并且比基于跟踪的方法使用的原始数据更少。我们通过优化全局对准问题来避免众所周知的环路闭合问题,同时计算所有扫描的变形,并使用尽可能严格的约束来消除变形形状的收缩问题,尤其是在变形的开放边界附近扫描。为了解决大规模问题,我们设计了一种从粗到细的多分辨率方案,该方案还避免了优化陷入局部极小值的情况。对公开数据集和由RGB-D传感器捕获的真实数据集评估了所提出的方法。实验结果表明,与几种最新方法相比,该方法获得了更好的结果。

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