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Automatic pose initialization of swimmers in videos

  • We propose an approach to the task of automatic pose initialization of swimmers in videos. Thus, our goal is to detect a swimmer inside a target video and assign an estimated position to her/his body parts. We first apply a non-skin-color filter to reduce the search space inside each target frame. We then match previously devised template sequences of Gaussian feature descriptors against sequences of feature vectors which are computed within the remaining image regions. Finally, relative average joint positions from annotated images featuring the key pose are assigned to the detection result and three-dimensional joint positions are estimated. We present detection results for test videos of three different swim strokes and examine the performance of four types of feature descriptors.

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Metadaten
Author:Christian X. Ries, Rainer LienhartORCiDGND
URN:urn:nbn:de:bvb:384-opus4-11182
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/1333
Series (Serial Number):Reports / Technische Berichte der Fakultät für Angewandte Informatik der Universität Augsburg (2009-19)
Type:Report
Language:English
Date of Publication (online):2009/11/17
Year of first Publication:2010
Publishing Institution:Universität Augsburg
Release Date:2009/11/17
Volume:2010
Edition:7543
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Maschinelles Lernen und Maschinelles Sehen
Nachhaltigkeitsziele
Nachhaltigkeitsziele / Ziel 3 - Gesundheit und Wohlergehen
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Deutsches Urheberrecht