The goal of this masters thesis was to design and implement a system that can process the video stream of a parking lot camera, extract locations of parking spots using the parked vehicles and determine the occupancy status of the parking lot.The system is composed of several services and a processing pipeline that periodically takes an image from the stream, locates the vehicles using object detector and performs time based sampling in order to filter out moving vehicles and eventually acknowledge the parking spots. Acknowledged parking spots are periodically evaluated for occupancy status by a custom classifier.
This system composes of several components that form a pipeline for evaluating a parking lot from a camera.
Images are taken from the camera specified for the parking lot and object detector is used to find locations of vehicles. Vehicles are used as a point of reference in order to get the parking spots. Parking spots are then classified on the newest snapshot from camera using custom trained classifier. Results are presented on a web page.
The source of the masters thesis can be found in following repo. https://github.com/grohj/Park-Detector-Thesis