Swimmer detection and pose estimation for continuous stroke rate determination

  • In this work we propose a novel approach to automatically detect a swimmer and estimate his/her pose continuously in order to derive an estimate of his/her stroke rate given that we observe the swimmer from the side. We divide a swimming cycle of each stroke into several intervals. Each interval represents a pose of the stroke. We use specifically trained object detectors to detect each pose of a stroke within a video and count the number of occurrences per time unit of the most distinctive poses (so-called key poses) of a stroke to continuously infer the stroke rate. We extensively evaluate the overall performance and the influence of the selected poses for all swimming styles on a data set consisting of a variety of swimmers.

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Metadaten
Author:Dan ZechaGND, Thomas GreifGND, Rainer LienhartGND
URN:urn:nbn:de:bvb:384-opus4-12389
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/1546
Series (Serial Number):Reports / Technische Berichte der Fakultät für Angewandte Informatik der Universität Augsburg (2011-13)
Publisher:Universität Augsburg
Place of publication:Augsburg
Type:Report
Language:English
Publishing Institution:Universität Augsburg
Release Date:2011/07/18
Tag:object detection; pose estimation; stroke rate estimation; swimming channel
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Multimedia und Maschinelles Sehen
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Deutsches Urheberrecht