Vision-based vehicle classification
Gupte, S.; Masoud, O.; Papanikolopoulos, P.
Intelligent Transportation Systems, 2000. Proceedings. 2000 IEEE
Volume , Issue , 2000 Page(s):46 - 51
Digital Object Identifier   10.1109/ITSC.2000.881016
Summary:This paper presents algorithms for vision-based detection and classification of vehicles in monocular image sequences of traffic scenes recorded by a stationary camera. Processing is done at three levels: raw images, blob level and vehicle level. Vehicles are modeled as rectangular patches with certain dynamic behavior. Kalman filtering is used to estimate vehicle parameters. The proposed method is based on the establishment of correspondences among blobs and vehicles, as the vehicles move through the image sequence. Experimental results from highway scenes are provided, which demonstrate the effectiveness of the method

» View citation and abstract

Log in by entering your IEEE Web Account Username and Password.

IEEE Communications Society members: If you subscribe to the IEEE Electronic Periodicals Package or IEEE Electronic Periodicals Package Plus, you must access your subscription at www.comsoc.org.

Check with your librarian, information professional, or system manager to determine if you need to log in. Please complete the online Technical Support Form if you need assistance.

Select the Purchase History link to access the document. You will have 5 Days after purchase to access the Full Text PDF. Please complete the online Technical Support Form if you need assistance.

• Search and access Abstract records free of charge
• Register for table of contents alerts
• Purchase Full Text PDF documents

» Learn more about subscription options or how to become an IEEE Member.