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首页> 外文期刊>Computer vision and image understanding >Coarse-to-fine surface reconstruction from silhouettes and range data using mesh deformation
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Coarse-to-fine surface reconstruction from silhouettes and range data using mesh deformation

机译：使用网格变形从轮廓和范围数据进行从粗到细的曲面重建

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摘要

We present a coarse-to-fine surface reconstruction method based on mesh deformation to build watertight surface models of complex objects from their silhouettes and range data. The deformable mesh, which initially represents the object visual hull, is iteratively displaced towards the triangulated range surface using the line-of-sight information. Each iteration of the deformation algorithm involves smoothing and restructuring operations to regularize the surface evolution process. We define a non-shrinking and easy-to-compute smoothing operator that fairs the surface separately along its tangential and normal directions. The mesh restructuring operator, which is based on edge split, collapse and flip operations, enables the deformable mesh to adapt its shape to the object geometry without suffering from any geometrical distortions. By imposing appropriate minimum and maximum edge length constraints, the deformable mesh, hence the object surface, can be represented at increasing levels of detail. This coarse-to-fine strategy, that allows high resolution reconstructions even with deficient and irregularly sampled range data, not only provides robustness, but also significantly improves the computational efficiency of the deformation process. We demonstrate the performance of the proposed method on several real objects.
机译：我们提出了一种基于网格变形的从粗糙到精细的表面重建方法，以根据其轮廓和距离数据构建复杂对象的水密表面模型。使用视线信息，将最初代表对象视觉船体的可变形网格迭代地移向三角测距表面。变形算法的每次迭代都涉及平滑和重构操作，以规范化表面演化过程。我们定义了一个非收缩且易于计算的平滑算子，该算子沿着曲面的切线方向和法线方向分别对曲面进行光顺。基于边缘分割，折叠和翻转操作的网格重组运算符使可变形网格能够使其形状适应对象几何形状，而不会遭受任何几何变形。通过施加适当的最小和最大边缘长度约束，可变形的网格（即对象表面）可以以不断增加的细节级别表示。这种从粗到细的策略，即使在缺乏和不规则采样的距离数据的情况下，也可以进行高分辨率重建，不仅具有鲁棒性，而且还大大提高了变形过程的计算效率。我们在几个真实对象上演示了该方法的性能。

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