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Impact of Multi-View Fusion and Biomechanical Modeling on Markerless Motion Tracking
IEEE Transactions on Bio-Medical Engineering
|October 15, 2025
Summary
Markerless motion capture methods were benchmarked, revealing multi-view systems offer higher accuracy than single-view. Biomechanical modeling did not significantly improve vision-only accuracy, highlighting tradeoffs for applications.
Area of Science:
- Biomechanics
- Computer Vision
- Motion Analysis
Background:
- Markerless motion tracking offers a scalable alternative to marker-based systems.
- Benchmarking emerging markerless solutions on a common dataset is needed to understand accuracy-complexity trade-offs.
Purpose of the Study:
- Evaluate thirteen single-view and two multi-view markerless motion capture methods against marker-based tracking.
- Assess the impact of biomechanical modeling on vision-only markerless systems.
Main Methods:
- Compared 15 markerless methods against marker-based tracking for lower-extremity kinematics.
- Collected data from 23 healthy adults performing walking and functional exercises using 20 infrared and 10 RGB cameras.
- Utilized the best single-view model (WHAM) to test biomechanical modeling (bioWHAM).
Main Results:
- Multi-view methods generally outperformed single-view methods.
- OpenCap (2 cameras) outperformed WHAM (single-view) by 1.7° (p < 0.0001).
- Theia3D (10 cameras) outperformed OpenCap by 1.3° (p < 0.0001).
- Biomechanical modeling (bioWHAM) did not consistently improve accuracy over WHAM, with median fluctuations under 1.7°.
Conclusions:
- Multi-view systems can enhance accuracy, but benefits must be weighed against complexity.
- Findings guide hardware, software, and accuracy trade-off considerations for markerless motion capture.
- Further innovation in multi-view fusion and biomechanical modeling integration is warranted.
