3D Skeleton Detection from Baseball Motion Capture Data with Driveline C3D
📰 Dev.to · YMori
Detect 3D skeletons from baseball motion capture data to analyze pitching biomechanics and correlate with pitch velocity
Action Steps
- Load baseball motion capture data using ezc3d
- Preprocess data with MediaPipe for 3D skeleton detection
- Analyze trunk rotation range and its correlation with pitch velocity using statistical methods
- Visualize the results to identify key biomechanical factors affecting pitch velocity
- Apply the insights to optimize athlete training programs and improve performance
Who Needs to Know This
Data scientists and biomechanics engineers can benefit from this technique to gain insights into athlete performance and optimize training programs. It can be applied in sports analytics and athlete development teams.
Key Insight
💡 Trunk rotation range is strongly correlated with pitch velocity (r=0.425)
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🏟️ Analyze baseball motion capture data to detect 3D skeletons and correlate trunk rotation with pitch velocity 📈
Key Takeaways
Detect 3D skeletons from baseball motion capture data to analyze pitching biomechanics and correlate with pitch velocity
Full Article
I analyzed pitching and hitting biomechanics using Driveline OpenBiomechanics C3D data, ezc3d, and MediaPipe. Trunk rotation range showed the strongest correlation with pitch velocity (r=0.425).
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