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Airborne image sequences provide useful data for monitoring traffic scenes in large complex urban environments. Tracking vehicles in these low frame rate images is challenging, because of abrupt motion and low resolution description of the targets. In this work, we propose a new particle based method for long-term tracking of multiple vehicles in airborne images. Our tracking system uses a vehicle-specific...
A new method for real-time detection and tracking of multiple moving vehicles from traffic video is proposed. This method first uses MoG and texture based model to extract foreground from the scene, then detect moving targets using a modified version of timed motion history image (tMHI), and finally uses Kalman prediction filter to track these targets, which the full moving trajectories of the targets...
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...
This paper presents an adaptive cruise control (ACC) and collision avoidance (CA) system for vehicle autonomous driving. The control scheme is designed to improve drivers' comfort during multi-vehicle driving situations and to completely avoid rear-end collision using severe braking and lane change maneuver. In order to create such an application, the proposed system consists of a longitudinal control...
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