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In this paper we present an effective real-time video surveillance system for real-life outdoor surveillance scenarios. The system is an integration of two subsystems: the static camera and moving one. The approaches employed address properly the challenges that might arise in a typical outdoor scene, such as local and global lighting changes, variations in objects' appearance and occlusions. Our...
Correlation based stereo vision has proven its power in commercially available driver assistance systems. Recently, real-time dense stereo vision has become available on inexpensive FPGA hardware. In order to manage the huge amount of data, a medium-level representation named “Stixel World” has been proposed for further analysis. In this representation the free space in front of the vehicle is limited...
Vehicle velocity estimation is an important aspect of intelligent transportation systems. Normally velocity is estimated using dedicated laser speed traps and Doppler radars. Recently, the use of cameras is becoming more common for the purpose of traffic surveillance and smart surveillance system. It is thus the aim of this paper to propose a method for vehicle speed estimation using these existing...
In several vehicle tracking and localization applications, the initial position of a vehicle may be given by GPS measurements or other means. However, the information required for accurate tracking after initialization may only be available intermittently or not at all. In this paper, we demonstrate that the indirect or error form of state variables can be used in accurate bearing only tracking of...
We present here a prototype of an algorithm for vehicle speed estimation. Different from previous approaches, our algorithm requires no road markers and fewer manual calibrations. Based on specific projection rules, we find a relation between the in-camera coordinate and the real world coordinate. A non-linear regression is employed to estimate the model parameters. This model enables us to estimate...
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...
In modern intelligent transportation systems, the video image vehicle detection system (VIVDS) is gradually becoming one of the popular methods at signalized traffic intersection due to its convenient installation and rich information content provided. However, in the current VIVDS, the camera usually is installed at the roadside poles or traffic light poles, which not only requires more than one...
This paper presents methods for vision-based detection and tracking of vehicles in monocular image sequences of traffic scenes recorded by a stationary camera. The goal of this research is to develop suitable methods for automatic visual traffic surveillance to perform detection, tracking and traffic parameter estimation of multiple vehicles in real time as well as tackle environment illumination...
In this paper we describe a multi-camera traffic monitoring system relying on the concept of probability fusion maps (PFM) to detect vehicles in a traffic scene. In the PFM, traffic images from multiple cameras are inverse perspective-mapped and registered onto a common reference frame, combining the multiple camera information to reduce the impact of occlusions. Although the unconstrained perspective...
This paper presents a simple implementation for unmarked road tracking. It is mainly based on the calculation of road vanishing point position relative to the vehicle. An algorithm is derived to calculate the vanishing point location. This algorithm is made robust by introducing solutions to noisy peeks, unbounded vanishing point location, and irrelevant lines. Also, the paper defines a method to...
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