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Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings Yes
Title CED: Color Event Camera Dataset
Organization Unit
Authors
  • Cedric Scheerlinck
  • Henri Rebecq
  • Timo Stoffregen
  • Nick Barnes
  • Robert Mahony
  • Davide Scaramuzza
Presentation Type paper
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
ISBN 978-1-7281-2506-0
Page Range 1684 - 1693
Event Title 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Event Type conference
Event Location Long Beach, CA, USA
Event Start Date July 16 - 2019
Event End Date July 17 - 2019
Publisher IEEE
Abstract Text Event cameras are novel, bio-inspired visual sensors, whose pixels output asynchronous and independent timestamped spikes at local intensity changes, called 'events'. Event cameras offer advantages over conventional frame-based cameras in terms of latency, high dynamic range (HDR) and temporal resolution. Until recently, event cameras have been limited to outputting events in the intensity channel, however, recent advances have resulted in the development of color event cameras, such as the Color-DAVIS346. In this work, we present and release the first Color Event Camera Dataset (CED), containing 50 minutes of footage with both color frames and events. CED features a wide variety of indoor and outdoor scenes, which we hope will help drive forward event-based vision research. We also present an extension of the event camera simulator ESIM that enables simulation of color events. Finally, we present an evaluation of three state-of-the-art image reconstruction methods that can be used to convert the Color-DAVIS346 into a continuous-time, HDR, color video camera to visualise the event stream, and for use in downstream vision applications.
Digital Object Identifier 10.1109/cvprw.2019.00215
Other Identification Number merlin-id:20291
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