Stryker is a state-of-the-art foosball analytics solution. With Stryker, foosball players can get important game statistics including game score, game clock, time of possession, and shot speeds, all updated in real-time. The Stryker software tracks the foosball game, updating a database with the real-time game statistics. We were inspired to make Stryker as a way to start learning about computer vision, and we thought that tracking our foosball table would be a great application.
The Stryker camera mount was built using telescoping PVC piping, allowing it to be attached to any foosball table. The computer vision software, built with Python and OpenCV, runs on a Raspberry Pi that mounts to the table. The computer vision software also directly updates Firebase. The web app, also connected to Firebase, allows players to monitor the game in real-time and make necessary adjustments.
One of the most difficult portions of this project was accurately filtering out noise while tracking the foosball. Accounting for various lighting conditions, camera obstacles, and camera framerate proved to be challenges that we gradually overcame by iteratively updating our thresholding.
In the future, we hope to add more detailed analysis capabilities to Stryker, including predictive shot tracking and individual player stats.