CUMULATIVE ASSESSMENT FOR URBAN 3D MODELING

Shea Hagstrom, Hee Won Pak, Stephanie Ku, Sean Wang, Gregory Hager, Myron Brown

Research output: Contribution to conferencePaperpeer-review

Abstract

Urban 3D modeling from satellite images requires accurate semantic segmentation to delineate urban features, multiple view stereo for 3D reconstruction of surface heights, and 3D model fitting to produce compact models with accurate surface slopes. In this work, we present a cumulative assessment metric that succinctly captures error contributions from each of these components. We demonstrate our approach by providing challenging public datasets and extending two open source projects to provide an end-to-end 3D modeling baseline solution to stimulate further research and evaluation with a public leaderboard.

Original languageEnglish (US)
Pages3261-3264
Number of pages4
DOIs
StatePublished - 2021
Event2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 - Brussels, Belgium
Duration: Jul 12 2021Jul 16 2021

Conference

Conference2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021
Country/TerritoryBelgium
CityBrussels
Period7/12/217/16/21

Keywords

  • Benchmarks
  • Metrics
  • Multiple view stereo
  • Semantic segmentation
  • Urban 3D modeling

ASJC Scopus subject areas

  • Computer Science Applications
  • General Earth and Planetary Sciences

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