Deep learning-based vehicle occupancy detection in an open parking lot using thermal camera

Vijay Paidi; Hasan Fleyeh; Roger G. Nyberg

Deep learning-based vehicle occupancy detection in an open parking lot using thermal camera

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Author(s): Vijay Paidi¹ ; Hasan Fleyeh¹ ; Roger G. Nyberg¹
- Affiliations: 1: Dalarna University, Faculty of Data & Information Sciences , Borlange , Sweden
Source: Volume 14, Issue 10, October 2020, p. 1295 – 1302
DOI: 10.1049/iet-its.2019.0468 , Print ISSN 1751-956X, Online ISSN 1751-9578

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)

Received 10/07/2019, Accepted 24/06/2020, Revised 13/05/2020, Published 03/08/2020

Parking has been a common problem over several years in many cities around the globe. The search for parking space leads to congestion, frustration and increased air pollution. Information of vacant parking space would facilitate to reduce congestion and subsequent air pollution. Therefore, the aim of the study is to acquire vehicle occupancy in an open parking lot using deep learning. Thermal camera was used to collect videos during varying environmental conditions and frames from these videos were extracted to prepare the dataset. The frames in the dataset were manually labelled as there were no pre-labelled thermal images available. Vehicle detection with deep learning algorithms was implemented to perform multi-object detection. Multiple deep learning networks such as Yolo, Yolo-conv, GoogleNet, ReNet18 and ResNet50 with varying layers and architectures were evaluated on vehicle detection. ResNet18 performed better than other detectors which had an average precision of 96.16 and log-average miss rate of 19.40. The detected results were compared with a template of parking spaces to identify vehicle occupancy information. Yolo, Yolo-conv, GoogleNet and ResNet18 are computationally efficient detectors which took less processing time and are suitable for real-time detection while Resnet50 was computationally expensive.

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Deep learning-based vehicle occupancy detection in an open parking lot using thermal camera

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