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Okutama-Action: An Aerial View Video Dataset for Concurrent Human Action Detection
KTH. Polytechnic University of Catalonia, Spain.
KTH, School of Computer Science and Communication (CSC).
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2017 (English)In: 30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017, IEEE Computer Society, 2017, Vol. 2017, 2153-2160 p.Conference paper (Refereed)
Abstract [en]

Despite significant progress in the development of human action detection datasets and algorithms, no current dataset is representative of real-world aerial view scenarios. We present Okutama-Action, a new video dataset for aerial view concurrent human action detection. It consists of 43 minute-long fully-annotated sequences with 12 action classes. Okutama-Action features many challenges missing in current datasets, including dynamic transition of actions, significant changes in scale and aspect ratio, abrupt camera movement, as well as multi-labeled actors. As a result, our dataset is more challenging than existing ones, and will help push the field forward to enable real-world applications.

Place, publisher, year, edition, pages
IEEE Computer Society, 2017. Vol. 2017, 2153-2160 p.
Series
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, ISSN 2160-7508 ; 2017
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:kth:diva-215882DOI: 10.1109/CVPRW.2017.267Scopus ID: 2-s2.0-85030250941ISBN: 9781538607336 (print)OAI: oai:DiVA.org:kth-215882DiVA: diva2:1149853
Conference
30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017, Honolulu, United States, 21 July 2017 through 26 July 2017
Note

QC 20171017

Available from: 2017-10-17 Created: 2017-10-17 Last updated: 2018-01-13Bibliographically approved

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Marti, MiquelMurray, Samuel
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf