SportAI: Real-Time Computer Vision & Biometric Analytics
Automated biomechanical analysis and ball-tracking computer vision pipelines analyzing live tennis and padel matches.
The Challenge
Analyzing athletic technique required expensive motion-capture rigs and hours of manual video review. The client required an AI pipeline that could extract 3D kinematic body landmarks from single standard smartphone or broadcast cameras in real time.
The Solution & Architecture
WDL engineered a custom deep learning pose estimation and temporal movement model optimized via TensorRT for GPU inference at 60 frames per second.
Project Metadata
Key Technical Capabilities Delivered
Architectural components engineered specifically to resolve the client's scaling hurdles.
3D Biomechanical Extraction
Reconstructs joint angles, hip rotation, and racket velocity from monocular camera feeds without requiring physical wearable sensors.
Immediate Technique Feedback
Instant video overlay graphics highlighting shot mechanics, ball strike contact points, and athletic balance.
Automated Match Highlights
Event detection models index rallies, aces, and tactical winners to automatically compile broadcast summaries.
Technologies Used
Build Fast, Scale Reliably
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Validate Data Strategy
Technical audit and architecture blueprint to validate pipeline viability.
Build Data MVP / Foundation
Production-ready automated pipeline and live analytics lakehouse delivered in just 20 days.