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2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)最新文献

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Logarithmically proportional objective function for planar surfaces recognition in 3D point cloud 三维点云中平面识别的对数比例目标函数
Pub Date : 2014-07-01 DOI: 10.1109/NaBIC.2014.6921891
Mosab Bazargani, L. Mateus, M. A. R. Loja
3D laser scanning is becoming a standard technology to generate building models of a facility's as-is condition. Since most constructions are constructed upon planar surfaces, recognition of them paves the way for automation of generating building models. This paper introduces a new logarithmically proportional objective function that can be used in both heuristic and metaheuristic (MH) algorithms to discover planar surfaces in a point cloud without exploiting any prior knowledge about those surfaces. It can also adopt itself to the structural density of a scanned construction. In this paper, a metaheuristic method, genetic algorithm (GA), is used to test this introduced objective function on a synthetic point cloud. The results obtained show the proposed method is capable to find all plane configurations of planar surfaces (with a wide variety of sizes) in the point cloud with a minor distance to the actual configurations.
3D激光扫描正在成为一项标准技术,用于生成设施现状的建筑模型。由于大多数结构都是在平面上构造的,因此对它们的识别为自动生成建筑模型铺平了道路。本文介绍了一种新的对数比例目标函数,该函数可用于启发式和元启发式(MH)算法来发现点云中的平面,而无需利用任何关于这些表面的先验知识。它还可以适应扫描结构的结构密度。本文采用一种元启发式方法——遗传算法(GA)在合成点云上对引入的目标函数进行了测试。结果表明,该方法能够在点云中找到各种尺寸的平面的所有平面构型,并且与实际构型的距离很小。
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引用次数: 1
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2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)
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