ARrow: A Real-Time AR Rowing Coach
Abstract
Rowing requires physical strength and endurance in athletes as well as a precise rowing technique. The ideal rowing stroke is based on biomechanical principles and typically takes years to master. Except for time-consuming video analysis after practice, coaches currently have no means to quantitatively analyze a rower's stroke sequence and body movement. We propose ARrow, an AR application for coaches and athletes that provides real-time and situated feedback on a rower's body position and stroke. We use computer vision techniques to extract the rower's 3D skeleton and to detect the rower's stroke cycle. ARrow provides visual feedback on three levels: Tracking of basic performance metrics over time, visual feedback and guidance on a rower's stroke sequence, and a rowing ghost view that helps synchronize the body movement of two rowers. We developed ARrow in close colaboration with international rowing coaches and demonstrate its usefulness in a user study with athletes and coaches.
BibTeX
@inproceedings {10.2312:evs.20231046,
booktitle = {EuroVis 2023 - Short Papers},
editor = {Hoellt, Thomas and Aigner, Wolfgang and Wang, Bei},
title = {{ARrow: A Real-Time AR Rowing Coach}},
author = {Iannucci, Elena and Chen, Zhutian and Armeni, Iro and Pollefeys, Marc and Pfister, Hanspeter and Beyer, Johanna},
year = {2023},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-219-6},
DOI = {10.2312/evs.20231046}
}
booktitle = {EuroVis 2023 - Short Papers},
editor = {Hoellt, Thomas and Aigner, Wolfgang and Wang, Bei},
title = {{ARrow: A Real-Time AR Rowing Coach}},
author = {Iannucci, Elena and Chen, Zhutian and Armeni, Iro and Pollefeys, Marc and Pfister, Hanspeter and Beyer, Johanna},
year = {2023},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-219-6},
DOI = {10.2312/evs.20231046}
}