Automotive
Object recognition and tracking system in real-time from on board cameras
About this project
Our client dealing with traffic security desired to enhance the possibility to recognize objects in the surrounding in real-time. Our challenge was to create a universal system to detect cars, people, and other obstacles based on the view from a camera installed in a vehicle.
Services
Fixed Price Project
Technologies
OpenVINO, Python, WebSockets, OpenCV, NumPy, GitLab
Our machine learning and artificial intelligence specialists were involved in this project. In the beginning, we got acquainted with the available technology solutions. After determining the requirements, we designed and implemented the system architecture.
Then we developed the appropriate algorithms based on available solutions from Intel and OpenVINO. The chosen solution ensured sharing of large amounts of heavy data between the backend and front-end in real-time. Our engineers implemented modern AI and ML solutions.
BCF was responsible for a key part of the project, namely building appropriate models for teaching ML based on the available videos. The team evaluated and technically validated modern ML ops systems to ensure the deployment of models on the fly with application continuity.
In this project, we created a universal library that became the basis of a system for recognizing people, cars, and other objects.
Our solution is based on artificial intelligence and machine learning algorithms that process real-time image data from a vehicle's onboard camera as it moves.
The developed system enables real-time object recognition using images from the onboard camera of a moving vehicle. The software can be used to assist with parking and avoiding obstacles while driving. Implementation of the solution will improve security and enhance driving in crowdy places and tight spaces.
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