Integrating Inverse Photogrammetry and a Deep Learning–Based Point Cloud Segmentation Approach for Automated Generation of BIM Models-Reference-Cited by-同舟云学术

Integrating Inverse Photogrammetry and a Deep Learning–Based Point Cloud Segmentation Approach for Automated Generation of BIM Models

Published:2023-09 Issue:9 Volume:149 Page:
ISSN:0733-9364
Container-title:Journal of Construction Engineering and Management
language:en
Short-container-title:J. Constr. Eng. Manage.

Author:

Xiang Zhongming¹,Rashidi Abbas²,Ou Ge³

Affiliation:

1. Transmission Line Engineer, Stantec, Salt Lake City, UT 84121 (corresponding author).

2. Assistant Professor, Dept. of Civil and Environmental Engineering, Univ. of Utah, Salt Lake City, UT 84112.

3. Assistant Professor, Dept. of Civil and Coastal Engineering, Univ. of Florida, Gainesville, FL 32603.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Strategy and Management,Industrial relations,Building and Construction,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JCEMD4.COENG-13020

Reference98 articles.

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3. Armeni I. S. Sax A. R. Zamir and S. Savarese. 2017. “Joint 2D-3D-semantic data for indoor scene understanding.” Preprint submitted Feburary 3 2017. http://arxiv.org/abs/1702.01105.

4. Autodesk. 2021. “The overview of plant 3D.” Accessed May 6 2021. https://www.autodesk.com/products/autocad/included-toolsets/autocad-plant-3d.

5. Image-Based Localization and Content Authoring in Structure-from-Motion Point Cloud Models for Real-Time Field Reporting Applications

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