DocumentCode :
3388087
Title :
Vehicle Make and Model Recognition in CCTV footage
Author :
Saravi, Sara ; Edirisinghe, Eran A.
Author_Institution :
Dept. of Comput. Sci., Loughborough Univ., Loughborough, UK
fYear :
2013
fDate :
1-3 July 2013
Firstpage :
1
Lastpage :
6
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.
Keywords :
closed circuit television; image recognition; image segmentation; object detection; road vehicles; traffic engineering computing; video signal processing; CCTV video footage; CPD; LESH; ROI; VMMR; coherent point drift; local energy shape histogram; region-of-interest segmentation; vehicle make-and-model recognition; Educational institutions; Image recognition; Image resolution; Image segmentation; CCTV Footage; CPD; Coherent Point Drift; LESH; Local Energy Shape Histogram; Make and Model Recognition; VMMR;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Signal Processing (DSP), 2013 18th International Conference on
Conference_Location :
Fira
ISSN :
1546-1874
Type :
conf
DOI :
10.1109/ICDSP.2013.6622720
Filename :
6622720
Link To Document :
بازگشت