Overview
Led the end-to-end development of a real-time computer vision system for football match analytics, combining OCR, object detection, tracking, classification, and classical CV techniques into a unified production pipeline.
Achievements
• Built a low-latency multi-module perception system operating in real time • Successfully combined deep learning and classical CV methods in a single pipeline • Reduced processing delay while maintaining high detection accuracy • Enabled automated extraction of structured match data from live video streams
Responsibilities
- Developed object detection and player tracking models
- Implemented OCR for scoreboard and broadcast overlays
- Designed a modular perception architecture for real-time inference
- Built and maintained the data labeling and validation pipeline
- Optimized system performance for stable real-time execution
This project was delivered by
Vladimir C.
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