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Shape from silhouette using topology-adaptive mesh deformation

机译:使用拓扑自适应网格变形从轮廓造型

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We present a computationally efficient and robust shape from silhouette method based on topology-adaptive mesh deformation, which can produce accurate, smooth, and topologically consistent 3D mesh models of complex real objects. The deformation scheme is based on the conventional snake model coupled with local mesh transform operations that control the resolution and uniformity of the deformable mesh. Based on minimum and maximum edge length constraints imposed on the mesh, we describe a fast collision detection method which is crucial for computational efficiency of the reconstruction process. The topology of the deformable mesh, which is initially zero genus, can be modified whenever necessary by merging operations in a controlled and robust manner by exploiting the topology information available in the silhouette images. The performance of the proposed shape from silhouette technique is demonstrated on several real objects.
机译:我们提出了一种基于轮廓的,基于拓扑的网格变形的轮廓线计算方法,该算法具有高效,鲁棒的形状,可以生成复杂的真实对象的精确,平滑和拓扑一致的3D网格模型。变形方案基于常规的蛇形模型,结合了控制可变形网格的分辨率和均匀性的局部网格变换操作。基于对网格施加的最小和最大边缘长度约束,我们描述了一种快速碰撞检测方法,该方法对于重建过程的计算效率至关重要。最初是零属的可变形网格的拓扑可以在必要时通过利用轮廓图像中可用的拓扑信息以受控和鲁棒的方式合并操作来进行修改。通过轮廓技术提出的形状的性能已在多个真实对象上得到了证明。

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