DocumentCode
457531
Title
Robust vehicle detection based on shadow classification
Author
Lee, Deaho ; Park, Youngtae
Author_Institution
Fac. of Gen. Educ., Kyung Hee Univ.
Volume
3
fYear
0
fDate
0-0 0
Firstpage
1167
Lastpage
1170
Abstract
The multi-level shadow classification has been shown to provide reliable information on the presence of vehicles in traffic scenes. The method is based on classifying the shadow shapes into six categories at each threshold level. Non-overlapping shadow shapes with higher priority are selected at each level. Shadow-reshaping capability makes the resulting shadow information robust to the variation of operating conditions. Unlike other approaches, vehicle movement information between frames is not utilized; thereby the traffic parameters can be measured quantitatively even when the vehicle movement is not observed. Also the detecting performance is not affected by the abrupt change of weather because background information is not utilized
Keywords
image classification; object detection; road vehicles; traffic engineering computing; multilevel shadow classification; reliable information; robust vehicle detection; shadow information; shadow-reshaping capability; traffic parameters; vehicle movement information; Automotive engineering; Cameras; Layout; Monitoring; Reliability engineering; Robustness; Shape; Traffic control; Vehicle detection; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location
Hong Kong
ISSN
1051-4651
Print_ISBN
0-7695-2521-0
Type
conf
DOI
10.1109/ICPR.2006.1018
Filename
1699733
Link To Document