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Suggestion for Camera Location in Monocular Markerless 3D Motion Capture System: Focused on Accuracy Comparison With Marker-Based System for Upper Limb Jointsoa mark
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Publication Year
2025-01-01
Journal
IEEE Access
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
IEEE Access, Vol.13, pp.47605-47616
Keyword
3D motion capturecorrelationmarker-basedmean absolute errormonocular markerlessrange of motion
Mesh Keyword
3D motion capture3D motion capture systemsCamera positionsCorrelationFlexion-extensionMarker-basedMarkerlessMean absolute errorMonocular markerlessRange-of-motion
All Science Classification Codes (ASJC)
Computer Science (all)Materials Science (all)Engineering (all)
Abstract
A markerless motion capture system that analyzes human movements without markers has emerged. However, most studies use 2D coordinates to track basic movements from fixed viewpoints, with limited research on joint movement accuracy based on camera angles. This study evaluates a monocular markerless 3D motion capture system’s accuracy from various RGB camera positions and identifies optimal placements by comparing it with a marker-based system. Ten male participants in their 20s performed clinical range of motion (ROM) tasks, and joint angles were measured from different camera positions. The mean absolute error (MAE) and Pearson correlation coefficient between the two systems were analyzed. The neck joint showed the highest accuracy at 0°, while 45° and 315° were viable for flexion/extension. The shoulder joint performed best at 135°, 180°, and 315°, while the elbow joint showed the highest accuracy at 90° and 135°. The wrist joint had the lowest accuracy, but considering its correlation with flexion/extension, the 0°, 90°, and 270° positions may still be viable. For comprehensive upper body analysis, positioning the camera at 45° or 315° ensures accurate neck assessment while enabling balanced evaluation of lateral flexion, abduction/adduction, and flexion/extension. Future research should improve estimation performance in cases of body occlusion by expanding datasets and refining algorithms. Additionally, analyzing tilt caused by distance variations and applying a correction ratio could help mitigate MediaPipe’s tilt issue. Identifying optimal camera placements can enhance the accuracy of monocular markerless 3D motion capture, supporting its broader clinical application.
ISSN
2169-3536
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/38198
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105001209087&origin=inward
DOI
https://doi.org/10.1109/access.2025.3547715
Journal URL
http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639
Type
Article
Funding
This work was supported by the \u2018\u2018Cooperative Research Program for Agriculture Science and Technology Development\u2019\u2019 Rural Development Administration, Republic of Korea, under Project PJ01709903.
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Jung, Myung-Chul Image
Jung, Myung-Chul정명철
Department of Industrial Engineering
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