Synthesising 2D Video from 3D Motion Data for Machine Learning Applications

Synthesising 2D Video from 3D Motion Data for Machine Learning Applications

To increase the utility of legacy, gold-standard, three-dimensional (3D) motion capture datasets for computer vision-based machine learning applications, this study proposed and validated a method to synthesise two-dimensional (2D) video image frames from historic 3D motion data. We applied the vide...

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Bibliographic Details
Main Authors: Marion Mundt, Henrike Oberlack, Molly Goldacre, Julia Powles, Johannes Funken, Corey Morris, Wolfgang Potthast, Jacqueline Alderson
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Sensors
Subjects:
synthesising video images
pose estimation
machine learning
biomechanics
3D motion data
Online Access:https://www.mdpi.com/1424-8220/22/17/6522

Internet

https://www.mdpi.com/1424-8220/22/17/6522

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