TY - GEN
T1 - Automatic 3d modeling of structural and mechanical components from point clouds
AU - Perez-Perez, Yeritza
AU - Golparvar-Fard, Mani
AU - El-Rayes, Khaled
N1 - Publisher Copyright:
© 2018 American Society of Civil Engineers (ASCE). All rights reserved.
PY - 2018
Y1 - 2018
N2 - 3D modeling of structural and mechanical components from point clouds is a time-consuming and error prone task. It usually involves experts to analyze a captured point cloud, segment and label it into meaningful components (e.g., pipe, ceiling, beam, column, floor, wall), and then fit solid geometry to these components. Despite a large body of research on Scan2BIM over the past few years, there is still a gap in knowledge on how automatically segmented point clouds can be labeled and merged into 3D surface representations. To address this gap, this paper presents a method that takes in a segmented and semantically labeled point cloud, with mechanical components, at a desired level of abstraction and fits in solid geometrical elements. The input model was automatically labeled using a recent method of jointly labeling point clouds based on their underlying semantic and geometrical representations. To fit solid geometric components, the method uses a multi-scale features extraction method to identify the segment cross-sections and centerlines. The centerlines are used to infer the connection types (e.g., elbow, coupling, union, or diverter tee) among all segments. The method then uses the center lines and the cross-section radius to fit non-uniform rational basis splines (NURBS) over the point cloud segments and then fits in cylindrical elements into the produced NURBS surfaces. The method is validated using six real-world point clouds and the experimental results are discussed in detail.
AB - 3D modeling of structural and mechanical components from point clouds is a time-consuming and error prone task. It usually involves experts to analyze a captured point cloud, segment and label it into meaningful components (e.g., pipe, ceiling, beam, column, floor, wall), and then fit solid geometry to these components. Despite a large body of research on Scan2BIM over the past few years, there is still a gap in knowledge on how automatically segmented point clouds can be labeled and merged into 3D surface representations. To address this gap, this paper presents a method that takes in a segmented and semantically labeled point cloud, with mechanical components, at a desired level of abstraction and fits in solid geometrical elements. The input model was automatically labeled using a recent method of jointly labeling point clouds based on their underlying semantic and geometrical representations. To fit solid geometric components, the method uses a multi-scale features extraction method to identify the segment cross-sections and centerlines. The centerlines are used to infer the connection types (e.g., elbow, coupling, union, or diverter tee) among all segments. The method then uses the center lines and the cross-section radius to fit non-uniform rational basis splines (NURBS) over the point cloud segments and then fits in cylindrical elements into the produced NURBS surfaces. The method is validated using six real-world point clouds and the experimental results are discussed in detail.
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U2 - 10.1061/9780784481264.049
DO - 10.1061/9780784481264.049
M3 - Conference contribution
AN - SCOPUS:85048660150
T3 - Construction Research Congress 2018: Construction Information Technology - Selected Papers from the Construction Research Congress 2018
SP - 501
EP - 511
BT - Construction Research Congress 2018
A2 - Wang, Chao
A2 - Berryman, Charles
A2 - Harris, Rebecca
A2 - Harper, Christofer
A2 - Lee, Yongcheol
PB - American Society of Civil Engineers
T2 - Construction Research Congress 2018: Construction Information Technology, CRC 2018
Y2 - 2 April 2018 through 4 April 2018
ER -