ACM SIGSPATIAL GISCUP 2022 Workshop Report: Extracting Building Footprints from LiDAR Point Clouds Seattle, Washington, USA, November 1, 2022-Reference-Cited by-同舟云学术

ACM SIGSPATIAL GISCUP 2022 Workshop Report: Extracting Building Footprints from LiDAR Point Clouds Seattle, Washington, USA, November 1, 2022

Published:2022-11 Issue:1 Volume:14 Page:51-55
ISSN:1946-7729
Container-title:SIGSPATIAL Special
language:en
Short-container-title:SIGSPATIAL Special

Author:

Brooks Cheryl¹,Isci Serkan²,Kanza Yaron¹,Klosowski James T.²,Woods Robert³

Affiliation:

1. AT&T Data Science and AI Research, USA

2. AT&T Labs-Research, USA

3. AT&T Chief Data Office, USA

Abstract

The 11 th SIGSPATIAL Cup competition, GISCUP 2022, was held in conjunction with the 30 th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2022), and focused on extraction of building footprints from LiDAR point clouds. Participating teams competed on computing the most accurate building footprints in selected areas, based on a given LiDAR point cloud. The point cloud was USGS data created by scanning the area using light detection and ranging. The top three teams presented their results at the SIGSPATIAL 2022 conference.

Publisher

Association for Computing Machinery (ACM)

Subject

General Medicine

Link

https://dl.acm.org/doi/pdf/10.1145/3632268.3632285

Reference16 articles.

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

5. Deep semantic segmentation for building detection using knowledge-informed features from LiDAR point clouds