An efficient method for producing deep learning point cloud datasets based on BIM 3D model and computer simulation

Heng Zhang; Tianyu Wang

doi:10.1117/12.2653608

8 December 2022 An efficient method for producing deep learning point cloud datasets based on BIM 3D model and computer simulation

Heng Zhang, Tianyu Wang

Author Affiliations +

Proceedings Volume 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022); 124740Z (2022) https://doi.org/10.1117/12.2653608
Event: Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 2022, Guilin, China

Abstract

Currently, 3D deep learning based on point cloud data has become a research hotspot in the field of computer vision. However, the high cost of acquiring point cloud data, the tedious process of processing and labeling, and the scarcity of high-quality and suitable datasets have been the prominent problems faced by researchers. In this paper, we propose a method to quickly produce point cloud dataset based on BIM 3D model and computer simulation technology, including the steps of classifying and labeling BIM models, converting 3D object data formats, extracting point clouds using Pytorch3d and Open3d libraries, and improving efficiency through Revit secondary development and Dos batch processing. Finally, we demonstrate the effectiveness of the method by performing semantic segmentation experiments using Pointnet++ network and analyzed the impact of point cloud sampling density, sampling method and 3D model accuracy on the performance of virtual point cloud. As a digital twin of the real world, BIM models are a natural database with rich scenes and all kinds of elements. It is hoped that the method studied in this paper can help researchers to produce datasets applicable to their own research and provide help for the application of 3D deep learning techniques in engineering and other fields.

Citation Download Citation

Heng Zhang and Tianyu Wang "An efficient method for producing deep learning point cloud datasets based on BIM 3D model and computer simulation", Proc. SPIE 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 124740Z (8 December 2022); https://doi.org/10.1117/12.2653608

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
14 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Clouds

3D modeling

Data modeling

Computer simulations

Data conversion

Data processing

Visualization

Show All Keywords

Keywords/Phrases

Search In:

Publication Years