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This paper presents an automatic traffic surveillance system which is utilized to monitor the traffic intersections. Moving vehicles are extracted accurately from video sequences based on improved background modeling and object tracking method. In this paper, 16 types of general traffic behaviors at intersections are specifically defined and the traffic information collected from the tracking results...
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...
On a moving vehicle, speedy motion extraction from video is demanded. Different from the traditional motion estimation methods that track or match 2D features in consecutive motion-blurred images, this work explores a novel approach to find motion without explicit shape analysis. We take spatial integration of intensities in each frame and the obtained consecutive profiles provide distinct motion...
In this paper, we have proposed an efficient vision based method for the tracking of flying vehicles via a moving video camera. The suggested approach is based on the combination of the feature extraction and matching algorithm as well as the 2D deformable mesh surfaces. We have developed a new set of energy functions for mesh to improve the performance and quality of the tracking algorithm. The proposed...
The classification and statistics of the vehicles type in the road section are important parameters for the traffic management and control. The paper put forward the vehicle classification using image invariant moment and BP neural networks. First of all, road background is rebuild according to the serials images, and the background differences are used to segment vehicle region, invariant moment...
This paper presents a novel technique to align partial 3D reconstructions of the seabed acquired by a stereo camera mounted on an autonomous underwater vehicle. Vehicle localization and seabed mapping is performed simultaneously by means of an Extended Kalman Filter. Passive landmarks are detected on the images and characterized considering 2D and 3D features. Landmarks are re-observed while the robot...
In this paper, we proposed an intelligent visual surveillance in specific sea-area based on video processing. We apply the technology of computer vision and video processing to implement the automatic system. At the first, we separate background and foreground in videos, and set a weight to update the new background. To extract the moving ships in videos, we apply the techniques including the change...
To discover important but previously unknown information in video sequences, a discovery method of unknown visual information based on target tracking is proposed in this paper. It provides a worthy approach for support decision. The proposed discovery method analyzes the video using target tracking. This method, adopting detection and correspondence of feature points, target identification and tracking,...
In surveillance applications, search space reduction (SSR) is an essential element to efficient algorithms. In this study, spatial and temporal SSRs are integrated for license plate detection in video sequences; the plates could be extracted robustly and extremely fast. Our method started from spatial SSR by a bi-level one-pass plate extraction (BOPE) algorithm developed to extract plates accurately...
Tracking vehicles in heavy-traffic video is a challenging problem. It is hard for algorithms based on background extraction to work well. We propose an algorithm that does not need background information. In this algorithm, vehicle corners are detected and tracked, and then grouped into vehicles. Experiments show the effectiveness of the proposed algorithm under heavy congestion.
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