Hierarchical model generation for architecture reconstruction using laser-scanned point clouds

Xiaojuan Ning; Yinghui Wang; Xiaopeng Zhang

doi:10.1117/1.OE.53.6.061612

20 January 2014 Hierarchical model generation for architecture reconstruction using laser-scanned point clouds

Xiaojuan Ning, Yinghui Wang, Xiaopeng Zhang

Author Affiliations +

Optical Engineering, Vol. 53, Issue 6, 061612 (January 2014). https://doi.org/10.1117/1.OE.53.6.061612

Abstract

Architecture reconstruction using terrestrial laser scanner is a prevalent and challenging research topic. We introduce an automatic, hierarchical architecture generation framework to produce full geometry of architecture based on a novel combination of facade structures detection, detailed windows propagation, and hierarchical model consolidation. Our method highlights the generation of geometric models automatically fitting the design information of the architecture from sparse, incomplete, and noisy point clouds. First, the planar regions detected in raw point clouds are interpreted as three-dimensional clusters. Then, the boundary of each region extracted by projecting the points into its corresponding two-dimensional plane is classified to obtain detailed shape structure elements (e.g., windows and doors). Finally, a polyhedron model is generated by calculating the proposed local structure model, consolidated structure model, and detailed window model. Experiments on modeling the scanned real-life buildings demonstrate the advantages of our method, in which the reconstructed models not only correspond to the information of architectural design accurately, but also satisfy the requirements for visualization and analysis.

Citation Download Citation

Xiaojuan Ning, Yinghui Wang, and Xiaopeng Zhang "Hierarchical model generation for architecture reconstruction using laser-scanned point clouds," Optical Engineering 53(6), 061612 (20 January 2014). https://doi.org/10.1117/1.OE.53.6.061612

Published: 20 January 2014

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