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

Master Thesis (2020)
Author(s)

G.M.W. Reichert (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

A Vilanova – Mentor (TU Delft - Computer Graphics and Visualisation)

R. Marroquim – Graduation committee member (TU Delft - Computer Graphics and Visualisation)

J.C. Gemert – Graduation committee member (TU Delft - Pattern Recognition and Bioinformatics)

Gert van der Heijden – Graduation committee member

Douwe Broekens – Graduation committee member

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2020 Gijs Reichert
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Gijs Reichert
Graduation Date
20-02-2020
Awarding Institution
Delft University of Technology
Faculty
Electrical Engineering, Mathematics and Computer Science
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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.

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