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In this paper, we address the problem of vehicle detection and tracking with low-angle cameras by combining windshield detection and feature points clustering, effectively fusing several primitive image features such as color, edge and interest point. By exploring various heterogenous features and multiple vehicle models, we achieve at least two improvements over the existing methods: higher detection...
Traditional vision based vehicle detection methods are more successful in detecting front and rear vehicles. However, the problem of detecting vehicles under various poses still presents a great deal of difficulty. Pose variation leads to limit the use of vision based driver assistance systems. In this paper, we present a Conditional Random Fields (CRFs) based algorithm that can detect vehicles under...
Due to the recent progress in computer vision to interpret images and sequence of images, the video camera is a promising sensor for traffic monitoring and traffic surveillance at low cost. This paper focuses on the detection and tracking of multiple vehicles present in the field of view of a camera. Until now, the vehicle detection has been mainly performed by the widely used technique called background...
Accurate lane detection in real-time is a critical task in autonomous vehicle guidance and lane departure warning for driver assistance. Existing vision-based approaches rely mostly on some analysis of the spatial gradient of the image. However, if the road structure is not regular and well delimited, edges may not be easy to extract and other features must be employed. This paper evaluates the use...
For realizability and real-time processing consideration, a novel vehicle classification method is proposed for heavy traffic flow multi-lanes roads, which can classify vehicles into cars, trucks and buses. In order to monitor two lanes, our system uses three cameras which are mounted overhead of the road and look down the road at an angle of about 60 degrees. Two of them focus on the two lanes respectively...
In modern societies, due to the high crime rates and high traffic accidents the feeling of insecurity and threat is increasing. The need for the establishment of defence and prevention mechanisms has encouraged studies to develop automatic recognition systems, which should, for example, have the ability to recognize vehicles at a certain distance.This paper introduces two car recognition methods,...
Video-based surveillance and measuring have been employed more and more widely in traffic monitoring system because of the rich information content contained in video. The vehicles need to be segmented from the video images, the result of vehicles segmentation using background subtraction is not only vehicles but also shadows of vehicles, a method of shadow removing based on texture analysis is presented...
The automatic lane marking detection, vehicle detection and incident detection systems are proposed in this paper. The block-based background extraction that combines statistical algorithm and the moving block information is used to obtain the color background image more exactly. The lane detection algorithm is applied to obtain the lane information from the color background image without the limitation...
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