Abstract
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 final 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.
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