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Illegally parked vehicle detection using deep learning and key-point tracking
conference contribution
posted on 2023-06-10, 05:54 authored by Xing Gao, Phil BirchPhil Birch, Rupert YoungRupert Young, Chris ChatwinChris ChatwinIn 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.
History
Publication status
- Published
File Version
- Accepted version
Journal
IET Conference PublicationsPublisher
Institution of Engineering and TechnologyExternal DOI
Issue
CP760Volume
2019Page range
7-12Event name
9th International Conference on Imaging for Crime Detection and Prevention (ICDP-2019)Event location
London UKEvent type
conferenceEvent date
16-18th December 2019ISBN
9781839531095Department affiliated with
- Engineering and Design Publications
Notes
This 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.Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2023-01-09First Open Access (FOA) Date
2023-01-11First Compliant Deposit (FCD) Date
2023-01-11Usage metrics
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