Markerless camera-based vertical jump height measurement using openpose

verfasst von

Fritz Webering, Holger Blume, Issam Allaham

Abstract

Vertical jump height is an important tool to measure athletes' lower body power in sports science and medicine. This work improves upon a previously published self-calibrating algorithm, which determines jump height using a single smartphone camera. The algorithm uses the parabolic fall trajectory obtained by tracking a single feature in a high-speed video. Instead of tracking an ArUco marker, which must be attached to the jumping subject, this work uses the OpenPose neural network for human pose estimation in order to calculate an approximation of the body center of mass. Jump heights obtained this way are compared to the reference heights from a motion capture system and to the results of the original work. The result is a trade-off between increased ease-of-use and slightly diminished accuracy of the jump height measurement.

Organisationseinheit(en)

Fachgebiet Architekturen und Systeme

Typ

Aufsatz in Konferenzband

Seiten

3863-3869

Anzahl der Seiten

7

Publikationsdatum

2021

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Maschinelles Sehen und Mustererkennung, Elektrotechnik und Elektronik

Ziele für nachhaltige Entwicklung

SDG 3 – Gute Gesundheit und Wohlergehen

Elektronische Version(en)

https://doi.org/10.15488/13695 (Zugang: Offen)
https://doi.org/10.1109/cvprw53098.2021.00428 (Zugang: Geschlossen)