Artificial Neural Network for Semantic Segmentation of Built Environments for Automated Scan2BIM

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

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

Abstract

3D modeling of the built environment has become common practice in the AEC/FM industry. Practitioners take advantage of the geometric and semantic information embedded in the 3D model to perform engineering analysis. Despite the benefits provide by the 3D model, the process is time-consuming, labor-intensive, and error-prone. In this paper, we propose a new neural network-based method for 3D point cloud semantic segmentation of building scenes using a hierarchical approach: first, we reason on the local and global contents of raw point cloud data to extract geometrical features. Second, the features are used as input to an artificial neural network that performs semantic segmentation on the points. These points are classified into: beam, ceiling, clutter, column, door, floor, pipe, wall, and window. We evaluated our approach on a dataset of several buildings and we obtained an accuracy of 73%. Our experiments produce robust results readily useful for practical Scan2BIM applications.

Original languageEnglish (US)
Title of host publicationComputing in Civil Engineering 2019
Subtitle of host publicationData, Sensing, and Analytics - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019
EditorsYong K. Cho, Fernanda Leite, Amir Behzadan, Chao Wang
PublisherAmerican Society of Civil Engineers
Pages97-104
Number of pages8
ISBN (Electronic)9780784482438
StatePublished - 2019
EventASCE International Conference on Computing in Civil Engineering 2019: Data, Sensing, and Analytics, i3CE 2019 - Atlanta, United States
Duration: Jun 17 2019Jun 19 2019

Publication series

NameComputing in Civil Engineering 2019: Data, Sensing, and Analytics - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019

Conference

ConferenceASCE International Conference on Computing in Civil Engineering 2019: Data, Sensing, and Analytics, i3CE 2019
CountryUnited States
CityAtlanta
Period6/17/196/19/19

ASJC Scopus subject areas

  • Computer Science(all)
  • Civil and Structural Engineering

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