DocumentCode :
2250845
Title :
Advanced framework for illumination invariant traffic density estimation
Author :
Janney, Pranam ; Geers, Glenn
Author_Institution :
Comput. Sci. & Eng., Univ. of New South Wales, Sydney, NSW, Australia
fYear :
2009
fDate :
4-7 Oct. 2009
Firstpage :
1
Lastpage :
6
Abstract :
CCTV cameras are becoming a common fixture at the roadside. Their use varies from traffic monitoring to security surveillance. In this paper an advanced two-stage framework for estimating vehicular traffic density on a road segment is presented. The proposed approach is computationally efficient and robust to varying illumination. The method is novel because it combines state-of-the-art image processing techniques with a simple traffic model in order to increase robustness. Experimental results have shown that the proposed framework can achieve higher performance than existing state-of-the-art techniques under conditions of varying illumination.
Keywords :
closed circuit television; image processing; image sensors; lighting; traffic engineering computing; video surveillance; CCTV cameras; illumination invariant traffic density estimation; image processing techniques; intelligent transportation systems; security surveillance; traffic monitoring; Cameras; Fixtures; Image segmentation; Lighting; Monitoring; Roads; Robustness; Security; Surveillance; Traffic control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation Systems, 2009. ITSC '09. 12th International IEEE Conference on
Conference_Location :
St. Louis, MO
Print_ISBN :
978-1-4244-5519-5
Electronic_ISBN :
978-1-4244-5520-1
Type :
conf
DOI :
10.1109/ITSC.2009.5309854
Filename :
5309854
Link To Document :
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