Article
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Preserved in Portico This version is not peer-reviewed
Parking Time Violation Tracking using Yolov8 and DeepSORT
Version 1
: Received: 10 May 2023 / Approved: 11 May 2023 / Online: 11 May 2023 (08:47:32 CEST)
A peer-reviewed article of this Preprint also exists.
Sharma, N.; Baral, S.; Paing, M.P.; Chawuthai, R. Parking Time Violation Tracking Using YOLOv8 and Tracking Algorithms. Sensors 2023, 23, 5843. Sharma, N.; Baral, S.; Paing, M.P.; Chawuthai, R. Parking Time Violation Tracking Using YOLOv8 and Tracking Algorithms. Sensors 2023, 23, 5843.
Abstract
In Thailand, parking time violation is a major problem, especially for mini-marts. At present the task of detecting parking time violation is mainly conducted manually using Closed-Circuit Television (CCTV). This method requires additional human labour to track incoming and outgoing vehicles. Therefore, low cost time violation tracking is needed. To the best of our knowledge, there has not been any research for parking violation detection and tracking conducted for parking time limits. This paper introduces a novel parking time violation detection algorithm using the Yolov8 and DeepSORT tracking algorithms to track vehicles in consecutive frames. The presented parking violation tracking algorithm can provide a guideline for research in parking time violation detection.
Keywords
DeepSORT; Object Detection; Parking Time Tracking; Parking Violation Detection; Vehicle Tracking, Yolov8
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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