Towards Parking Lot Occupancy Assessment Using Aerial Imagery and Computer Vision
Abstract
Advances in Computer Vision and Aerial Imaging have enabled countless downstream applications. To this end, aerial imagery could be leveraged to analyze the usage of parking lots. This would enable retail centres to allocate space better and eliminate the parking oversupply problem. With this use case in mind, the proposed research introduces a novel framework for parking lot occupancy assessments. The framework consists of a pipeline of components that map a sequence of image sets spanning a parking lot at different time intervals to a parking lot turnover heatmap that encodes the frequency each parking stall was used. The pipeline of components includes Image Stitching, Vehicle Detection and Heatmap Generation. The focus of this work is Image Stitching and Vehicle Detection, while Heatmap Generation is left for future work. Beyond proposing a novel framework for parking lot occupancy assessments, several contributions are made to the Computer Vision field. In particular, a novel method for initializing the pose of images based on the metadata from the acquisition system is introduced. Additionally, a novel comparative study of object detection models applied to the vehicle detection task is presented. Extensive experiments are used to validate the proposed contributions on both public and private datasets.