This paper presents a novel approach to Vehicle Make & Model Recognition in CCTV video footage. CPD (coherent Point Drift) is used to effectively remove skew of vehicles detected as CCTV cameras are not specifically configured for the VMMR (Vehicle Make and Model Recognition) task and may capture vehicles at different approaching angles. Also a novel ROI (Region Of Interest) segmentation is proposed. A LESH (Local Energy Shape Histogram) feature based approach is used for vehicle make and model recognition with the novelty that temporal processing is used to improve reliability. A number of further algorithms are used to maximize the reliability of the fnal outcome. Experimental results are provided to prove that the proposed system demonstrates accuracy over 95% when tested in real CCTV footage with no prior camera calibration.
History
School
Science
Department
Computer Science
Published in
2013 18th International Conference on Digital Signal Processing, DSP 2013
Citation
SARAVI, S. and EDIRISINGHE, E., 2013. Vehicle make and model recognition in CCTV footage. IN: Proceedings of 2013 18th International Conference on Digital Signal Processing (DSP 2013), Santorini, Greece, 1-3 July 2013, DOI: 10.1109/ICDSP.2013.6622720.
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/