Parking Time Violation Tracking using Yolov8 and DeepSORT

dc.contributor.authorNabin Sharma
dc.contributor.authorSushish Baral
dc.contributor.authorMay Phu Paing
dc.contributor.authorRathachai Chawuthai
dc.date.accessioned2025-07-21T06:09:12Z
dc.date.issued2023-05-11
dc.description.abstractIn 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.
dc.identifier.doi10.20944/preprints202305.0828.v1
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/12452
dc.subjectTracking (education)
dc.subject.classificationSmart Parking Systems Research
dc.titleParking Time Violation Tracking using Yolov8 and DeepSORT
dc.typePreprint

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