Soccer Player Identification in Live Streams
Wasiq Malik
• R&D for a novel deep-learning solution to the problem of real-time identification of soccer players in
live/broadcast videos.
• Created an In-house Soccer players dataset extracted from Premier League and LaLiga videos.
• Developed a real-time player tracking pipeline in GPU-accelerated PyTorch using DeepSort with
YOLOv5 backend, reaching over 85% accuracy.
• Implemented Jersey number detection using YOLOv5, fine-tuned on our Soccer Player Dataset,
achieving over 90% accuracy.
• Implemented Jersey number recognition using ResNet trained on SVHN and fine-tuned on our
Dataset, achieving 87% accuracy.
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Posted Apr 28, 2024
R&D for a novel deep-learning solution to the problem of real-time identification of soccer players in live/broadcast videos.
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