DocumentCode
1943564
Title
Real-Time On-Road Vehicle Detection Combining Specific Shadow Segmentation and SVM Classification
Author
Liu, Xin ; Dai, Bin ; He, Hangen
Author_Institution
Inst. of Autom., Nat. Univ. of Defense Technol., Changsha, China
fYear
2011
fDate
5-7 Aug. 2011
Firstpage
885
Lastpage
888
Abstract
This paper presents a vision-based real-time vehicle detection approach. Combining segmenting the specific shadow area underneath the vehicle and using SVM-based classifier, the proposed approach is accurate and efficient for intelligent vehicle. Experiment results with test dataset from real traffic scenes on freeways and urban roads are presented to illustrate the performance of this approach.
Keywords
image classification; image segmentation; object detection; support vector machines; traffic engineering computing; SVM classification; freeways; intelligent vehicle; specific shadow segmentation; urban roads; vision-based real-time vehicle detection approach; Feature extraction; Image edge detection; Intelligent vehicles; Real time systems; Traffic control; Vehicle detection; Vehicles; IntelLigent Vehicle; SVM; Vehicle Detection; Vehicle Shadow Segmentation; Vision;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Manufacturing and Automation (ICDMA), 2011 Second International Conference on
Conference_Location
Zhangjiajie, Hunan
Print_ISBN
978-1-4577-0755-1
Electronic_ISBN
978-0-7695-4455-7
Type
conf
DOI
10.1109/ICDMA.2011.219
Filename
6052052
Link To Document