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The TUM-DLR Multimodal Earth Observation Evaluation Benchmark

  • Tobias Koch
  • , Pablo Dangelo
  • , Franz Kurz
  • , F. Fraundorfer
  • , Peter Reinartz
  • , Marco Korner
  • Technical University of Munich
  • Deutsches Zentrum für Luft- und Raumfahrt (DLR)
  • Graz University of Technology (TU Graz)

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

9 Scopus citations

Abstract

We present a new dataset for development, benchmarking, and evaluation of remote sensing and earth observation approaches with special focus on converging perspectives. In order to provide data with different modalities, we observed the same scene using satellites, airplanes, unmanned aerial vehicles (UAV), and smartphones. The dataset is further complemented by ground-truth information and baseline results for different application scenarios. The provided data can be freely used by anybody interested in remote sensing and earth observation and will be continuously augmented and updated.

Original languageEnglish
Title of host publicationProceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016
PublisherIEEE Computer Society
Pages698-705
Number of pages8
ISBN (Electronic)9781467388504
DOIs
StatePublished - 16 Dec 2016
Event29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016 - Las Vegas, United States
Duration: 26 Jun 20161 Jul 2016

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516

Conference

Conference29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016
Country/TerritoryUnited States
CityLas Vegas
Period26/06/161/07/16

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