NCTU-GTAV360: A 360° Action Recognition Video Dataset

Sandy Ardianto, Hsueh Ming Hang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Despite many action recognition video datasets available right now, none of them are in the spherical projection. NCTU-GTAV360 is a new 360° action recognition video dataset captured from a game, Grand Theft Auto V (GTA V). The spherical video is obtained by stitching 24 views from various angles and combining them into a video. The benefit of using 360° cameras is that it can capture the entire surroundings using one single camera. We captured 200 locations within the Los Santos city (city name in the GTA V). This dataset should benefit researchers working on the spherical images, particularly the human action recognition research using machine learning or deep learning technique, which requires a large amount of training data and the associated ground-truth.

Original languageEnglish
Title of host publicationIEEE 21st International Workshop on Multimedia Signal Processing, MMSP 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728118178
DOIs
StatePublished - Sep 2019
Event21st IEEE International Workshop on Multimedia Signal Processing, MMSP 2019 - Kuala Lumpur, Malaysia
Duration: 27 Sep 201929 Sep 2019

Publication series

NameIEEE 21st International Workshop on Multimedia Signal Processing, MMSP 2019

Conference

Conference21st IEEE International Workshop on Multimedia Signal Processing, MMSP 2019
CountryMalaysia
CityKuala Lumpur
Period27/09/1929/09/19

Keywords

  • action recognition dataset
  • person detection
  • spherical video
  • vehicle detection

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  • Cite this

    Ardianto, S., & Hang, H. M. (2019). NCTU-GTAV360: A 360° Action Recognition Video Dataset. In IEEE 21st International Workshop on Multimedia Signal Processing, MMSP 2019 [8901740] (IEEE 21st International Workshop on Multimedia Signal Processing, MMSP 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MMSP.2019.8901740