A visual analysis framework for dinghy sailing: Towards leveraging recorded training sessions

Master thesis (2020)

Authors

G.M.W. Reichert Electrical Engineering, Mathematics and Computer Science

Contributors

A. Vilanova Bartroli Computer Graphics and Visualisation - EEMCS (mentor)
Ricardo Marroquim Computer Graphics and Visualisation - EEMCS (graduation committee member)
J.C. van Gemert Pattern Recognition and Bioinformatics - EEMCS (graduation committee member)
Gert van der Heijden (graduation committee member)
Douwe Broekens (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2020 Gijs Reichert
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Published Date

20-02-2020

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Nowadays video plays an important role in the coaching of athletes across many different sports. To make more use of the advantages videos can provide for coaching, the Dutch Sailing team is shifting from manually recording short videos towards continuously recording training sessions. This new recording approach provides opportunities and creates challenges at the same time. In this thesis we present a pipeline to address the problems with the stability of the recording and the first steps towards a Visual Analysis Framework, which leverages the available video data. New information is extracted from the video recordings by detecting and tracking the boat and sailors. Moreover, we semi-automatically highlight interesting intervals in time of a recorded training session. These are the first steps towards an extensive Visual Analysis Framework which has the potential to make the analysis of the videos easier and provide the coaches with tools to improve the analysis of the performance of the sailors.