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Run spot run: capturing and tagging footage of a race by crowds of spectators

Flintham, Martin D.; Velt, Raphael; Wilson, Max L.; Anstead, Edward J.; Benford, Steve; Brown, Anthony; Pearce, Timothy; Price, Dominic; Sprinks, James

Authors

Martin D. Flintham

Raphael Velt

Edward J. Anstead

STEVE BENFORD steve.benford@nottingham.ac.uk
Dunford Chair in Computer Science

Anthony Brown

Timothy Pearce

James Sprinks



Abstract

There has been a massive growth in the number of people who film and upload amateur footage of events to services such as Facebook and Youtube, or even stream live to services such as LiveStream. We present an exploratory study that investigates the potential of these spectators in creating footage en masse; in this case, during a live trial at a local marathon. We deployed a prototype app, RunSpotRun, as a technology probe to see what kinds of footage spectators would produce. We present an analysis of this footage in terms of its coverage, quality, and contents, and also discuss the implications for a) spectators enjoying the race, and b) extracting the stories of individual runners throughout the race. We conclude with a discussion of the challenges that remain for deploying such technology at a larger scale.

Citation

Flintham, M. D., Velt, R., Wilson, M. L., Anstead, E. J., Benford, S., Brown, A., …Sprinks, J. (2015). Run spot run: capturing and tagging footage of a race by crowds of spectators. In CHI '15: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 747-756. doi:10.1145/2702123.2702463

Conference Name Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems
Start Date Apr 18, 2015
End Date Apr 23, 2015
Publication Date Apr 20, 2015
Deposit Date Jan 22, 2016
Publisher Association for Computing Machinery (ACM)
Peer Reviewed Peer Reviewed
Pages 747-756
Series Title CHI '15
Book Title CHI '15: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems
ISBN 978-1-4503-3145-6
DOI https://doi.org/10.1145/2702123.2702463
Keywords crowd sourcing, marathon, public settings, story telling, tagging, video
Public URL http://eprints.nottingham.ac.uk/id/eprint/31319
Publisher URL https://dl.acm.org/citation.cfm?doid=2702123.2702463
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf
Additional Information Published in: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15). New York : ACM, 2015. ISBN 9781450331456, pp. 747-756. DOI: 10.1145/2702123.2702463