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
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;
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
DOI :
10.1109/ICDMA.2011.219
