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Shot speed prediction using object tracking for Passion Football
The ICONS app by Passion Football lets football players of all levels develop their skills and challenge others. We developed a solution that uses the smartphone camera to track and accurately estimate a players shot speed.
With the app, users can access a variety of exercises that measure essential football skills. These exercises are designed to be both fun and interactive, while also providing analytical insights to the player and suggesting exercises that target and improve their weak areas.
On-device, real time car fuel lid detection
We developed a CPU-optimized object detection model for on-device detection of fuel lids on cars.
The model was integrated into the central control system of the fueling rig, taking the role of the main detection mechanism, firstly to make sure the car is in the right position, and secondly to guide the fueling arm to the fuel door lid in real-time.When optimizing the model for CPU inference, we explored TensorFlow Lite and OpenVINO. In the end, we used OpenVINO which is a framework for optimizing deep neural nets on Intel CPU’s.
Real-time object detection for online gaming tournaments
Abios Gaming is a startup that focuses on tracking real-time events in online gaming tournament video streams. They asked us to improve detection performance and make previously impossible detections, possible.
Among the objects to be tracked were various weapons and tools the players use in-game, as well as certain interactions. The system detects and tracks timestamped events in correspondence with the objects the players possess, or use, to provide a structured stream of events that captures essential information about the evolution of the tournament.
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