Swimmer localization from a moving camera

Sha, Long, Lucey, Patrick J., Morgan, Stuart, Pease, Dave, & Sridharan, Sridha (2013) Swimmer localization from a moving camera. In de Souza, Paulo, Engelke, Ulrich, & Rahman, Ashfaqur (Eds.) Proceedings of the 2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA), IEEE, Wrest Point, Hobart, TAS, pp. 200-207.

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At the highest level of competitive sport, nearly all performances of athletes (both training and competitive) are chronicled using video. Video is then often viewed by expert coaches/analysts who then manually label important performance indicators to gauge performance. Stroke-rate and pacing are important performance measures in swimming, and these are previously digitised manually by a human. This is problematic as annotating large volumes of video can be costly, and time-consuming. Further, since it is difficult to accurately estimate the position of the swimmer at each frame, measures such as stroke rate are generally aggregated over an entire swimming lap. Vision-based techniques which can automatically, objectively and reliably track the swimmer and their location can potentially solve these issues and allow for large-scale analysis of a swimmer across many videos. However, the aquatic environment is challenging due to fluctuations in scene from splashes, reflections and because swimmers are frequently submerged at different points in a race. In this paper, we temporally segment races into distinct and sequential states, and propose a multimodal approach which employs individual detectors tuned to each race state. Our approach allows the swimmer to be located and tracked smoothly in each frame despite a diverse range of constraints. We test our approach on a video dataset compiled at the 2012 Australian Short Course Swimming Championships.

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ID Code: 66579
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Vision-based techniques, Swimmer localization, Moving camera, Aquatic environment, Reliably track the swimmer, Multimodal approach, Individual detectors
DOI: 10.1109/DICTA.2013.6691533
ISBN: 9781479921263
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 by the Institute of Electrical and Electronic Engineers, Inc. All rights reserved.
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Deposited On: 23 Jan 2014 22:38
Last Modified: 29 Jan 2014 04:58

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