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Future digital avionics systems will work in complex and cluttered environments which require systems engineering solutions for such applications as airport ground surface management. In this paper, we highlight the use of a L1 video tracker for monitoring activities at an airport. We present methods of information fusion, entity detection, and activity analysis using airport videos for runway detection...
This paper proposed an accurate shadow removal method for vehicle tracking. Firstly we detect and remove the shadow using optical gain based gradient analysis,in this process some parts of vehicle which are similar to shadow region in color space may be detected as shadow and removing these parts will leave some holes in the vehicle region. Then we fill these holes using the skeleton information of...
Event detection is an important research in video surveillance technology. This paper proposed a method for traffic event detection based on visual Mechanism on the background of traffic video surveillance applications. In this method, based on the extraction of video target motion characteristics, it extracted abnormal targets mainly through the features merging and significant competitive in video...
This paper presents a complete system for accurately and efficiently counting vehicles in a highway surveillance video. The proposed approach employs vehicle detection and tracking modules. In the detection module, an automatically trained binary classifier detects vehicles while providing robustness against view-point, poor quality videos and clutter. Efficient tracking is then achieved by a simplified...
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...
Forewarning to avoid potential traffic accidents is of great importance for Intelligent Transportation Systems (ITS). Under pedestrian and vehicle mixed traffic conditions like urban road intersections, traffic monitoring and forewarning have especially important values. Therefore in this paper a novel urban traffic information analysis and forewarning system is presented. Our system contains modules...
This paper presents a joint probabilistic relation graph approach to simultaneously detect and track a large number of vehicles in low frame rate aerial videos. Due to low frame rate, low spatial resolution and sheer number of moving objects, detection and tracking in wide area video poses unique challenges. In this paper, we explore vehicle behavior model from road structure and generate a set of...
As traffic surveillance technologies continue to grow worldwide, vehicle detection, counting and tracking are becoming increasing important. This paper proposes a real-time multi-vehicle detection and tracking approach. Lane marker detection is carried out for vehicle counting on each lane. It also helps remove the foreground noise and shadow. Instead of tracking the entire vehicle blob, vehicle sub-feature...
Video traffic surveillance is of high interest in the field of intelligent transportation systems and the moving vehicle tracking is an essential technique. Particle filter approximate the optimal Bayesian solution for vehicle tracking as a nonlinear or non-Gaussian system. In this paper a vehicle tracking method based on PF is presented, which combines gray and contour feature particles using fusion...
In this paper, Adopt a way that combines with Mean Shift algorithm and Kalman filter to tracking moving vehicle in the paper. At first, Using inter-frame difference algorithm to extract aimed-vehicle. After the aimed-vehicle is processed by binarization and mathematics morphology, we adopt Kalman filter to predict the position of vehicle. Then we adopt Mean shift algorithm to iterate and compute the...
Accurate object tracking is a challenging problem in visual surveillance due to noise segmentation, partial and full object occlusions. In this paper, we present a method for object tracking and primitive event detection by associating tracklet caused by these problems. The aim is to keep track identity across tracking gaps and detect object's motion changes (identify primitive event) that cause tracklet...
Automated tracking of vehicles and people is essential for the effective utilization of imagery in wide area surveillance applications. In order to determine the best tracking algorithm and parameters for a given application, a comprehensive evaluation procedure is required. However, despite half a century of research in multi-target tracking, there is no consensus on how to score the overall performance...
This paper presents an integrated solution for vehicle's velocity estimation and vehicle counting. The proposed restores the scene geometric properties, building a ground plane rectified image. Moreover, multiple vehicles tracking is performed embedding the concept of region covariance descriptors in a particle filter framework. The results show the effectiveness of the approach here proposed in very...
Geospatial video surveillance network (GVSN) is an effective remote sensing approach for urban security and emergency applications. In this paper, the GVSN system could be separated into four basic functional parts that include change detection, object recognition, target tracking and target positioning. Each part has its special utility to solve the security and emergency problems. When the functions...
Recently video surveillance techniques have been widely applied to intelligent transportation systems. Tracking of moving objects such as vehicles has become a major topic in video surveillance applications. This paper presents a multi-feature fusion model based on a particle filter for moving object tracking. The particle filter combines color and edge orientation information by a stochastic fusion...
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