20 January 2014 Hierarchical model generation for architecture reconstruction using laser-scanned point clouds
Author Affiliations +
Optical Engineering, 53(6), 061612 (2014). doi: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.
© 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)
Xiaojuan Ning, Yinghui Wang, Xiaopeng Zhang, "Hierarchical model generation for architecture reconstruction using laser-scanned point clouds," Optical Engineering 53(6), 061612 (20 January 2014). http://dx.doi.org/10.1117/1.OE.53.6.061612
JOURNAL ARTICLE
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KEYWORDS
3D modeling

Clouds

Buildings

Data modeling

Image segmentation

Optical engineering

Reconstruction algorithms

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