Convolutional Neural Network Architecture for Semantic Labeling Structural and Mechanical Elements

Yeritza Perez-Perez, Mani Golparvar-Fard, Khaled El-Rayes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The generation of 3D solid models from point cloud data can be a time-consuming, labor-intensive, and error-prone task. Architects, engineers, and contractors are taking advantage of the information embedded in 3D solid models to manage infrastructures during its entire life (planning, construction, operation, and maintenance). Several research groups have developed new methods with the objective of identifying the elements present in the building scenes. Despite the progress made by them, the existing methods require a significant amount of manual interaction and fail to represent structural or mechanical components when these are in close proximity to other components. To address these limitations, this paper presents a new method for semantically segment point cloud scene containing structural and mechanical components (e.g., beams, ceilings, columns, floors, pipes, and walls). The point cloud is semantically segmented using a convolutional neural network (CNN) architecture that identifies the semantic category that the point cloud points belong. The method was tested using six real-world point clouds, and the method obtained an average point accuracy of 90.23%. The experimental results showed robust results for Scan2BIM applications.

Original languageEnglish (US)
Title of host publicationConstruction Research Congress 2020
Subtitle of host publicationComputer Applications - Selected Papers from the Construction Research Congress 2020
EditorsPingbo Tang, David Grau, Mounir El Asmar
PublisherAmerican Society of Civil Engineers
Pages1336-1345
Number of pages10
ISBN (Electronic)9780784482865
StatePublished - 2020
Externally publishedYes
EventConstruction Research Congress 2020: Computer Applications - Tempe, United States
Duration: Mar 8 2020Mar 10 2020

Publication series

NameConstruction Research Congress 2020: Computer Applications - Selected Papers from the Construction Research Congress 2020

Conference

ConferenceConstruction Research Congress 2020: Computer Applications
Country/TerritoryUnited States
CityTempe
Period3/8/203/10/20

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction

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