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This paper proposed a new technique to determine the direction of a moving vehicle. In order to detect vehicles from road, concept of symmetrical descriptor is used to determine the ROI of each vehicle without using any motion features. This scheme proved to be advantageous as it does not require any background subtraction and efficiently works on real time applications. Once the vehicle is detected,...
Detecting an illegally parked vehicle in urban scenes of traffic monitoring system becomes more complex task due to occlusions, lighting changes, and other factors. In this paper, a new framework to detect illegally parked vehicle using dual background model subtraction is presented. In our system, the adaptive background model is generated based on statistical information of pixel intensity that...
Driving assistance system has a significant influence on driving safety, and we introduce an integrated Forward Collision Warning(FCW) system based on monocular vision. In order to reduce the searching region of original image, lane making is presented to establish the ROI firstly. Secondly, hypotheses are extracted using Haar-like feature and Adaboost classifier. To remove false positive detection...
SURF (Speeded Up Robust Features) is a robust and useful feature detector for various vision-based applications but lacks the ability to detect symmetrical objects. This paper proposes a new symmetrical SURF descriptor to enrich the power of SURF to detect all possible symmetrical matching pairs through a mirroring transformation. A vehicle make-and-model recognition (MMR) application is then adopted...
A novel approach to detect vehicles in night outdoor scenes is proposed in this paper. By using online subspace learning, the preliminary foreground is obtained based on spatio-temporal bricks. Meanwhile, a new operator named 3DLBP is proposed to describe the local features of bricks. The final foreground is acquired by region-grow with 3DLBP and preliminary foreground. The results of experiment indicate...
In this paper, we present improved lane tracking using vehicle localization. Lane markers are detected using a bank of steerable filters, and lanes are tracked using Kalman filtering. On-road vehicle detection has been achieved using an active learning approach, and vehicles are tracked using a Condensation particle filter. While most state-of-the art lane tracking systems are not capable of performing...
This paper describes a real-time vehicle recognition system in which the basic components of road vehicles are first located in the video sequence images based on background subtraction and then Harris corner of moving vehicles are abstracted. At last, we calculate the Hausdorff distance between the Harris corner of which need to be recognized and that of standard samples of car, bus and truck. The...
A method to detect moving vehicles in airborne video is proposed in this paper. In order to deal with moving object detection in non-stationary background, the global motion of background is estimated frame by frame according to the correspondence control points extracted by Harris feature point extraction algorithm. The relative position of the feature points is used to remove the inadequate point...
This paper presents a robust method for real-time vehicle detection and tracking in dynamic traffic environments. The proposed strategy aims to find a trade-off between the robustness shown by time-uncorrelated detection techniques and the speed-up obtained with tracking algorithms. It combines both advantages by continuously evaluating the quality of the tracking results along time and triggering...
In recent days, various in-vehicle camera systems have been proposed for detecting following vehicles. In this paper, we propose a vehicle detection method based on feature points. First, the feature points are detected from the image obtained from the camera and the optical flow is calculated by tracking the feature points across the image sequence. Then the feature points are assumed to be coplanar...
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