Football Analytics Machine Vision
Bringing Professional-Level Football Analytics to Amateur Clubs with AI-Powered Video Tracking
problem
The client, a US company specializing in applications for non-professional athletes to track their progress and achievements, faced a challenge in bringing professional-level football analytics to amateur clubs. They aimed to streamline coaching, player development, and recruitment processes by introducing an easy-to-use solution equipped with two cameras and cloud-based analytics.
problem
The client, a US company specializing in applications for non-professional athletes to track their progress and achievements, faced a challenge in bringing professional-level football analytics to amateur clubs. They aimed to streamline coaching, player development, and recruitment processes by introducing an easy-to-use solution equipped with two cameras and cloud-based analytics.
solution
Our team tackled this challenge by implementing a custom video analytics platform, leveraging its capabilities for people detection and tracking on football fields while gathering comprehensive statistics. The solution seamlessly integrates video, GPS sensors, and artificial intelligence into an intuitive application, comprising three main components: the people tracking system, ball tracking system, and pattern recognition system. Processing two 2.7K video streams at 20 frames per second (FPS) with over 80% accuracy on NVidia GTX 1080 Ti, the platform is further enhanced with personal GPS trackers, ensuring nearly 100% accuracy.
solution
Our team tackled this challenge by implementing a custom video analytics platform, leveraging its capabilities for people detection and tracking on football fields while gathering comprehensive statistics. The solution seamlessly integrates video, GPS sensors, and artificial intelligence into an intuitive application, comprising three main components: the people tracking system, ball tracking system, and pattern recognition system. Processing two 2.7K video streams at 20 frames per second (FPS) with over 80% accuracy on NVidia GTX 1080 Ti, the platform is further enhanced with personal GPS trackers, ensuring nearly 100% accuracy.
results
The core of our solution lies in the video analytics platform, encompassing three key components tailored to the unique demands of football environments. People tracking was optimized for accuracy and performance, utilizing techniques like slicing high-quality panoramic images for enhanced player position data. Ball tracking presented a significant challenge due to the ball's high speed and small size, but our R&D team developed a novel model based on fast-moving object detection technology. Finally, pattern recognition was achieved by training models to interpret football match events mathematically, based on behavior, relative positions, and object interactions, enabling the system to recognize patterns akin to human observers.
results
The core of our solution lies in the video analytics platform, encompassing three key components tailored to the unique demands of football environments. People tracking was optimized for accuracy and performance, utilizing techniques like slicing high-quality panoramic images for enhanced player position data. Ball tracking presented a significant challenge due to the ball's high speed and small size, but our R&D team developed a novel model based on fast-moving object detection technology. Finally, pattern recognition was achieved by training models to interpret football match events mathematically, based on behavior, relative positions, and object interactions, enabling the system to recognize patterns akin to human observers.
tech stack
tech stack
