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Height and Facet Extraction from LiDAR Point Cloud for Automatic Creation of 3D Building Models

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SIGSPATIAL '19: Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

Pages 596 - 599

https://doi.org/10.1145/3347146.3359372

Published: 05 November 2019 Publication History

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Abstract

Three-dimensional models of buildings have a variety of applications, e.g., in urban planning, for making decision where to locate power lines, solar panels, cellular antennas, etc. Often, 3D models are created from a LiDAR point cloud, however, this presents three challenges. First, to generate maps at a nationwide scale or even for a large city, it is essential to effectively store and process the data. Second, there is a need to produce a compact representation of the result, to avoid representing each building as thousands of points. Third, it is often required to seamlessly integrate computed models with non-geospatial features of the geospatial entities.

In this paper, we demonstrate an end-to-end automation of a large-scale 3D-model creation for buildings. The tool compacts the point cloud and allows to effortlessly integrate the results with information stored in a database. The main motivation for our tool is 5G network planning, where antenna locations require careful consideration, given that buildings and trees could obstruct or reflect high-frequency cellular transmissions.

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Czapiga KIsci SJaved MKanza YKounev VMeempat G(2024)Simulating Diffraction by Ray Tracing for Modeling 5G NetworksProceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems10.1145/3678717.3691267(661-664)Online publication date: 29-Oct-2024
https://dl.acm.org/doi/10.1145/3678717.3691267
Brooks CIsci SKanza YKlosowski JWoods R(2023)ACM SIGSPATIAL GISCUP 2022 Workshop Report: Extracting Building Footprints from LiDAR Point Clouds Seattle, Washington, USA, November 1, 2022SIGSPATIAL Special10.1145/3632268.363228514:1(51-55)Online publication date: 7-Nov-2023
https://dl.acm.org/doi/10.1145/3632268.3632285
Wang ZIsci SKanza YKounev VShaqalle Y(2023)Cellular Network Optimization by Deep Reinforcement Learning and AI-Enhanced Ray TracingProceedings of the 2nd ACM SIGSPATIAL International Workshop on Spatial Big Data and AI for Industrial Applications10.1145/3615888.3627814(41-50)Online publication date: 13-Nov-2023
https://dl.acm.org/doi/10.1145/3615888.3627814
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Index Terms

Height and Facet Extraction from LiDAR Point Cloud for Automatic Creation of 3D Building Models
1. Information systems
  1. Information systems applications
    1. Spatial-temporal systems

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Published In

SIGSPATIAL '19: Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 2019

648 pages

ISBN:9781450369091

DOI:10.1145/3347146

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 05 November 2019

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SIGSPATIAL '19: 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 5 - 8, 2019

IL, Chicago, USA

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SIGSPATIAL '19 Paper Acceptance Rate 34 of 161 submissions, 21%;

Overall Acceptance Rate 257 of 1,238 submissions, 21%

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Czapiga KIsci SJaved MKanza YKounev VMeempat G(2024)Simulating Diffraction by Ray Tracing for Modeling 5G NetworksProceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems10.1145/3678717.3691267(661-664)Online publication date: 29-Oct-2024
https://dl.acm.org/doi/10.1145/3678717.3691267
Brooks CIsci SKanza YKlosowski JWoods R(2023)ACM SIGSPATIAL GISCUP 2022 Workshop Report: Extracting Building Footprints from LiDAR Point Clouds Seattle, Washington, USA, November 1, 2022SIGSPATIAL Special10.1145/3632268.363228514:1(51-55)Online publication date: 7-Nov-2023
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Wang ZIsci SKanza YKounev VShaqalle Y(2023)Cellular Network Optimization by Deep Reinforcement Learning and AI-Enhanced Ray TracingProceedings of the 2nd ACM SIGSPATIAL International Workshop on Spatial Big Data and AI for Industrial Applications10.1145/3615888.3627814(41-50)Online publication date: 13-Nov-2023
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