The ball-pivoting algorithm for surface reconstruction
The ball-pivoting algorithm for surface reconstruction
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DOI：
10.1109/2945.817351
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发表时间：
1999-10-01
影响因子：
5.2
通讯作者：
Taubin, G
中科院分区：
文献类型：
--
作者：
Bernardini, F;Mittleman, J;Taubin, G
球旋转算法（BPA）计算一个三角形网格内插一个给定的点云。通常，这些点是利用物体的多次范围扫描获取的表面样本。BPA的原理非常简单：如果用户指定半径rho的球接触三个点而不包含任何其他点，则三个点形成三角形。从种子三角形开始，球围绕边缘枢转（即，它围绕边旋转，同时与边的端点保持接触），直到它接触另一个点，形成另一个三角形。该过程继续，直到所有可到达的边都已被尝试，然后从另一个种子三角形开始，直到所有点都已被考虑。然后可以用较大半径的球重复该过程以处理不均匀的采样密度。我们将BPA应用于数百万个点的数据集，这些点代表复杂3D对象的实际扫描。BPA所需的内存量相对较小，其时间效率和所获得的结果的质量与现有技术相比毫不逊色。
The Ball-Pivoting Algorithm (BPA) computes a triangle mesh interpolating a given point cloud. Typically, the points are surface samples acquired with multiple range scans of an object. The principle of the BPA is Very simple: Three points form a triangle if a bail of a user-specified radius rho touches them without containing any other point. Starting with a seed triangle, the bail pivots around an edge (i.e., it revolves around the edge while keeping in contact with the edge's endpoints) until it touches another point, forming another triangle. The process continues until all reachable edges have been tried, and then starts from another seed triangle, until all points have been considered. The process can then be repeated with a ball of larger radius to handle uneven sampling densities. We applied the BPA to datasets of millions of points representing actual scans of complex 3D objects. The relatively small amount of memory required by the BPA, its time efficiency, and the quality of the results obtained compare favorably with existing techniques.