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Illegally parked vehicle detection using deep learning and key-point tracking
conference contributionposted on 2023-06-10, 05:54 authored by Xing Gao, Phil BirchPhil Birch, Rupert YoungRupert Young, Chris ChatwinChris Chatwin
In this paper, we present a method for identifying and tracking illegally parked vehicles. This approach is based on deep learning for vehicles detection and hand crafted descriptors for the tracking which are designed to cope with occlusions. The tracking of the parked vehicle is achieved by key-point extraction of the detected vehicles and feature point matching. For each frame, a bounding box was generated to represent the vehicle and feature points extracted in that area. All parked vehicles have a unique ID which was generated by the Hungarian algorithm and Kalman ?lter, and the parked vehicle with the same ID was matched frame by frame. Based on this matching result, the stationary vehicles in the forbidden area can be tracked. Our approach tested ef?ciency and robustness on a public database and is shown to produce state of the art results.
- Accepted version
JournalIET Conference Publications
PublisherInstitution of Engineering and Technology
Event name9th International Conference on Imaging for Crime Detection and Prevention (ICDP-2019)
Event locationLondon UK
Event date16-18th December 2019
Department affiliated with
- Engineering and Design Publications
NotesThis paper is a postprint of a paper submitted to and accepted for publication in IET Conference Publications and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Library.
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