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Feasibility and Accuracy of an RTMPose-Based Markerless Motion Capture System for Single-Player Tasks in 3x3
Wen Zheng1,2,3, Mingxin Zhang1,2,3, Rui Dong4
1School of Athletic Performance, Shanghai University of Sport, Shanghai 200438, China.
Sensors (Basel, Switzerland)
|July 12, 2025
Summary
Markerless motion capture (MMC) provides a valid, non-invasive way to track basketball player movements. This study confirms its accuracy for assessing performance in 3x3 basketball drills.
Area of Science:
- Sports Science
- Biomechanics
- Performance Analysis
Background:
- Markerless motion capture (MMC) is a non-invasive technique for monitoring external load in sports.
- Its application and accuracy in 3x3 basketball contexts are not yet established.
- Wearable devices are often restricted in basketball, highlighting the need for alternative monitoring methods.
Purpose of the Study:
- To evaluate the viability and measurement precision of a multi-camera RTMPose-based MMC system for single-player 3x3 basketball tasks.
- To validate the system's accuracy in capturing key movement metrics relevant to basketball performance.
- To determine if MMC can reliably track player movements in an outdoor basketball setting.
Main Methods:
- Eight cameras (60 fps) recorded ten collegiate athletes performing basketball-specific drills (sprints, T-tests, jumps) on a half-court.
- 3D coordinates of hip and ankle keypoints were reconstructed using Direct Linear Transformation (DLT).
- Horizontal displacement and average speed were derived and validated against tape-measure and time-motion analysis.
Main Results:
- The MMC system showed high accuracy with coefficients of variation (CVs) under 5% and mean bias below 3.5%.
- Speed estimates demonstrated excellent consistency with time-motion analysis (ICC = 0.97-1.00).
- Bland-Altman analysis confirmed minimal bias and no proportional error.
Conclusions:
- The RTMPose-based MMC system is a consistent and accurate non-invasive method for collecting movement data in 3x3 basketball.
- This technology can be effectively used for single-player performance monitoring in outdoor basketball environments.
- Future research should investigate system performance during live play with multiple athletes and compare it to laboratory-grade systems.

