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Advisor(s)
Abstract(s)
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. © 2014 IEEE.
Description
Keywords
Genetic Algorithm Logarithmic Objective Function Planar Surface Recognition Point Cloud
Citation
BAZARGANI, Mosab; MATEUS, Luís; LOJA, Maria Amélia Ramos – Logarithmically proportional objective function for planar surfaces recognition in 3D point cloud. In 6th World Congress on Nature and Biologically Inspired Computing, NaBIC. New York : IEEE - Institute of Electrical and Electronics Engineers Inc., 2014. ISBN: 978-147995937-2. Art. nr. 6921891, pp. 275-280
Publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.