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Evaluating 3D Human Motion Capture using Apple ARKit against the Vicon System: A Dataset

Authors: Reimer, Lara Marie; Kapsecker, Maximilian; Fukushima, Takashi; Jonas, Stephan M.;

Evaluating 3D Human Motion Capture using Apple ARKit against the Vicon System: A Dataset

Abstract

A journal paper which was published in Applied Sciences gives detailed information about the dataset. Reimer, L.M.; Kapsecker, M.; Fukushima, T.; Jonas, S.M. Evaluating 3D Human Motion Capture on Mobile Devices. Appl. Sci. (2022) https://www.mdpi.com/2076-3417/12/10/4806 Please cite the corresponding paper when using the dataset. A dataset containing anonymized exercise data for eight exercises from ten subject. The exercise data was recorded with two iPads 11" (2021 version, Apple Inc., Cupertino, CA, USA) and a Vicon system. The two iPads were positioned frontal and in a 30° angle to the left side of the subject. The Vicon system used 14 cameras and captured the motion using the Full-body Plug-in-gait model. The dataset contains 220 files, 22 per subject. The structure of the dataset contains 10 folders, one per subject. Each folder contains two subfolders: ARKit and Vicon. Each ARKit folder holds two CSV files. Each Vicon folder holds 16 files, two per exercise: a .csv file with the motion data and a .xcp file containing meta data about the recording, including the camera setup and start/stop timestamps. Du to export problems, the ARKit files for the Side View do not always contain all joint data. The upper body joints are only available for three out of the ten subjects for the Side View.

This work was supported by a grant from Software Campus through the German Federal Ministry of Education and Research, grant number 01IS17049.

Keywords

mHealth, mobile motion capture, human motion capture, consumer electronics, dHealth, optical motion capture

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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