Automatic Detection and Segmentation of Columns in As-Built Buildings from Point Clouds

Remote Sensing

Lucía Díaz-Vilariño¹  Borja Conde¹  Susana Lagüela¹  Henrique Lorenzo¹  Devrim Akca² 

[1] Applied Geotechnologies Research Group, University of Vigo. Rúa Maxwell s/n, Campus Lagoas-Marcosende, Vigo 36310, Spain; E-Mails:Applied Geotechnologies Research Group, University of Vigo. Rúa Maxwell s/n, Campus Lagoas-Marcosende, Vigo 36310, Spain;

关键词: Terrestrial Laser Scanner;    point cloud;    building modelling;    segmentation;    feature extraction;    columns;    construction monitoring;    BIM;   

DOI  :  10.3390/rs71115651

来源: mdpi

【 摘 要 】

Over the past few years, there has been an increasing need for tools that automate the processing of as-built 3D laser scanner data. Given that a fast and active dimensional analysis of constructive components is essential for construction monitoring, this paper is particularly focused on the detection and segmentation of columns in building interiors from incomplete point clouds acquired with a Terrestrial Laser Scanner. The methodology addresses two types of columns: round cross-section and rectangular cross-section. Considering columns as vertical elements, the global strategy for segmentation involves the rasterization of a point cloud onto the XY plane and the implementation of a model-driven approach based on the Hough Transform. The methodology is tested in two real case studies, and experiments are carried out under different levels of data completeness. The results show the robustness of the methodology to the presence of clutter and partial occlusion, typical in building indoors, even though false positives can be obtained if other elements with the same shape and size as columns are present in the raster.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.