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This paper proposes a vision-based vehicle surveillance system for parking lot management in outdoor environments. Due to the limited field of view of camera, this system uses multiple cameras for monitoring a wide parking area. Then, an affine transformation is used for merging the scenes obtained from these multiple cameras. Two major components are included, i.e., vehicle counting and parking lot...
Vision based vehicle detection attracts much attention in low-altitude platform for urban traffic surveillance which has great potential practical value. The major difficulties of moving vehicle detection are two-fold: 1) the unconstrained motion of the camera platform; 2) crowded vehicles are connected and hard to be segmented. To address these problems, we proposed an improved registration method...
Due to the traffic accidents over the last few years; the development of surveillance systems with multifunctional techniques has received increasing attention. The use of the smart camera is one solution to solve the traffic problems, Smart cameras are cameras that can perform tasks far beyond simply taking photos and recording videos. Highways Traffic Surveillance System (HTSS) is used to monitor...
Automatic detection of vehicle incident by computer vision is one of the most important fields of video surveillance. In this paper, we propose a plane-geometry model to understand the vehicle behavior based on the visual information. The geometrical center of the vehicle-in-video object has different characters in different incidents. The vehicle objects of video are obtained by a background modeling...
This paper proposes an analysis method based on movement string for behavior understanding. Trajectories are analyzed by the improved principal component analysis (PCA) method which introduces the trajectory location and direction. Trajectory location and direction are the main features of PCA for scene division and Gaussian mixture hidden Markov model. With the help of these two features, we can...
This paper presents a novel approach to vehicle detection in highway surveillance videos. This method incorporates well-studied computer vision and machine learning techniques to form an unsupervised system, where vehicles are automatically ldquolearnedrdquo from video sequences. First an enhanced adaptive background mixture model is used to identify positive and negative examples. Then a classifier...
One key goal of current Computer Vision research activities is to provide robust systems for improving Transport safety through the use of Information Technology. Recent advances allow public environments (such as train stations or, simply, the street) under video surveillance to be modelled by means of the detection, tracking, and identification of the different elements in it (passengers, road,...
Camera calibration, as a fundamental issue in computer vision, is indispensable in many visual surveillance applications. Firstly, calibrated camera can help to deal with perspective distortion of object appearance on image plane. Secondly, calibrated camera makes it possible to recover metrics from images which are robust to scene or view angle changes. In addition, with calibrated cameras, we can...
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