Litcius/Paper detail

Point cloud segmentation and classification of structural elements in multi-planar masonry building facades

Fatemeh Hamid-Lakzaeian

2020Automation in Construction33 citationsDOIOpen Access PDF

Abstract

Multi-planar building facades, pose significant challenges to existing point cloud segmentation techniques, as most have an underlying assumption that all structural elements appear within only a single plane, which is often untrue. For architecturally complex buildings, this prevents the automatic extraction of the load bearing structure for use in structural engineering applications. To address these deficits, the multi-planar algorithm is introduced as a means to differentiate between structural and non-structural elements for multi-planar facades. The algorithm considers statistically the position of groups of points with respect to their neighbours to identify and segregate the principal facade of architecturally ornate, multi-planar buildings. The viability and robustness of the algorithm is demonstrated through its application to 3 buildings in Dublin, Ireland, which when compared to independent survey data, resulted in 98% accuracy for single complex openings and an overall average accuracy of at least 91%. The superiority of the technique is demonstrated against four prominent segmentation techniques and through the application of the output files into an ANSYS finite element model.

Topics & Concepts

FacadeMasonryPoint cloudSegmentationRobustness (evolution)Building modelPlanarStructural engineeringComputer sciencePosition (finance)Point (geometry)Artificial intelligenceEngineeringSimulationComputer graphics (images)GeometryMathematicsBiochemistryEconomicsFinanceGeneChemistry3D Surveying and Cultural HeritageRemote Sensing and LiDAR ApplicationsInfrastructure Maintenance and Monitoring
Point cloud segmentation and classification of structural elements in multi-planar masonry building facades | Litcius