Automatic 3D building model generation using deep learning methods based on cityjson and 2D floor plans

Richard Kippers*, M.N. Koeva, Maurice van Keulen, S.J. Oude Elberink

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

In the past decade, a lot of effort is put into applying digital innovations to building life cycles. 3D Models have been proven to be efficient for decision making, scenario simulation and 3D data analysis during this life cycle. Creating such digital representation of a building can be a labour-intensive task, depending on the desired scale and level of detail (LOD). This research aims at creating a new automatic deep learning based method for building model reconstruction. It combines exterior and interior data sources: 1) 3D BAG, 2) archived floor plan images. To reconstruct 3D building models from the two data sources, an innovative combination of methods is proposed. In order to obtain the information needed from the floor plan images (walls, openings and labels), deep learning techniques have been used. In addition, post-processing techniques are introduced to transform the data in the required format. In order to fuse the extracted 2D data and the 3D exterior, a data fusion process is introduced. From the literature review, no prior research on automatic integration of CityGML/JSON and floor plan images has been found. Therefore, this method is a first approach to this data integration.

Original languageEnglish
Title of host publicationThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
EditorsL. Truong-Hong, E. Che, F. Jia, S. Emamgholian, D. Laefer, A.V. Vo
PublisherCopernicus
Pages49-54
Number of pages6
VolumeXLVI-4-W4
DOIs
Publication statusPublished - 7 Oct 2021
Event16th 3D GeoInfo Conference 2021 - Virtual Conference, New York, United States
Duration: 11 Oct 202114 Oct 2021
Conference number: 16
https://3dgeoinfo2021.github.io/

Publication series

NameInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
PublisherCopernicus
ISSN (Print)1682-1750

Conference

Conference16th 3D GeoInfo Conference 2021
Country/TerritoryUnited States
CityNew York
Period11/10/2114/10/21
Internet address

Keywords

  • deep learning
  • 3D city models
  • ITC-GOLD

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