Swimmer detection and pose estimation for continuous stroke-rate determination

Dan Zecha; Thomas Greif; Rainer Lienhart

doi:10.1117/12.908309

9 February 2012 Swimmer detection and pose estimation for continuous stroke-rate determination

Dan Zecha, Thomas Greif, Rainer Lienhart

Proceedings Volume 8304, Multimedia on Mobile Devices 2012; and Multimedia Content Access: Algorithms and Systems VI; 830410 (2012) https://doi.org/10.1117/12.908309
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States

Abstract

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.

Citation Download Citation

Dan Zecha, Thomas Greif, and Rainer Lienhart "Swimmer detection and pose estimation for continuous stroke-rate determination", Proc. SPIE 8304, Multimedia on Mobile Devices 2012; and Multimedia Content Access: Algorithms and Systems VI, 830410 (9 February 2012); https://doi.org/10.1117/12.908309

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