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In this paper a new approach aimed at automatic identify events of abandoned and stolen objects detection in video surveillance system is described. Our method mainly includes three steps of data processing: the first processing phrase is object extraction, involving a background subtraction algorithm which dynamically updates two sets of background. Then, extracted objects are classified as static...
Camera networks are important in a video surveillance system. Many surveillance systems research has been done; most of it utilizes a general purpose computer. However, the latest trend is to use small, task specific and low power computer to process and control the system; in another word using embedded systems. This paper presents a camera network localization algorithm to be implemented on a FPGA...
Real-time video processing is the basic requirement for applications such as video surveillance, traffic management and medical imaging. The high computation power is a requirement to support this operation. This requirement could be fulfilled by utilizing the hardware accelerator architecture for computation part. This paper presents the development of edge detection hardware accelerator architecture...
The image pipeline play a key role in improving the quality of color video image from the cmos/ccd image sensor in video surveillance system. The proposed pipeline is composed of automatic white balance, CFA color interpolation and illumination reducing. The automatic white balance module can reduce the color cast of one image which is undercoloured. By calculating the direction of centered pixel,...
Recent advances in electronics and sensor design have enabled the development of a hyperspectral video camera that can capture hyperspectral datacubes at near video rates. The sensor offers the potential for novel and robust methods for surveillance by combining methods from computer vision and hyperspectral image analysis. Here, we focus on the problem of tracking objects through challenging conditions,...
This paper presents a fast background estimation method for vehicle surveillance based on multi-resolution analysis (MRA) and block updating strategy. Firstly, an approximate expression of original image is achieved by (MRA) and the feature difference is calculated along adjacent frames to divide the foreground and background; Secondly, the isolated pixels are removed by morphologic operation; and...
To test the vehicle license plate area is a main task based on video surveillance in ITS, especially for high-resolution video streams, now many kinds of methods are invalid for their complexity and slow speed. In this paper a new method was proposed to accomplish this task based on convolution energy. Firstly set an approximate detection area and generate brightness curve from the difference image...
A novel framework for anomaly detection in crowded scenes is presented. Three properties are identified as important for the design of a localized video representation suitable for anomaly detection in such scenes: (1) joint modeling of appearance and dynamics of the scene, and the abilities to detect (2) temporal, and (3) spatial abnormalities. The model for normal crowd behavior is based on mixtures...
In this work, we propose a feedback scheme for simultaneous thermal-visible video registration, sensor fusion, and tracking for online video surveillance applications. The video registration is based on a RANSAC trajectory-to-trajectory matching that estimates an affine transformation matrix that maximizes the corresponding trajectory points and overlapping of foreground thermal and visible pixels...
Background modeling plays an important role in video surveillance, yet in complex scenes it is still a challenging problem. Among many difficulties, problems caused by illumination variations and dynamic backgrounds are the key aspects. In this work, we develop an efficient background subtraction framework to tackle these problems. First, we propose a scale invariant local ternary pattern operator,...
We present a novel method for the discovery and statistical representation of motion patterns in a scene observed by a static camera. Related methods involving learning of patterns of activity rely on trajectories obtained from object detection and tracking systems, which are unreliable in complex scenes of crowded motion. We propose a mixture model representation of salient patterns of optical flow,...
Human detection and tracking is a primary focus for visual surveillance systems. However, current systems for human tracking are often complex and require vast amounts of computing resources. A reduction in complexity of the overall tracking system can be achieved by using a System of Systems (SoS) architecture. Once formed, a SoS architecture must achieve desirable levels of interoperability and...
With the rapid development of science and technology and with the continuous improvement of people's safe sense, Video Surveillance System has already been widely used in several fields, such as military affairs, production, daily life and so on. As the most basic and important part of Video Surveillance System, the detection of moving objects has been paid more attention. Therefore, this paper mainly...
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...
This paper aims at developing a flexible video analysis system that can be used in wide range of video surveillance applications as well as to detect the human being. The developed system is called here as Smart Video Analysis System. This SVAS is able to detect and track interested objects. It can also detect people and recognize their activities in an application environment, such as in a room,...
Recent research in video surveillance system has shown an increasing focus on creating reliable systems utilizing non-computationally expensive technique for observing humans' appearance, movements and activities, thus providing analytical information for advanced human behaviour analysis and realistic human modelling. In order for the system to function, it requires robust method for detecting human...
This paper introduces an embedded architecture and the low-level video processing algorithms developed for an intelligent node that is a part of a distributed intelligent sensory network for surveillance purposes. In this paper, details of the architecture developed for this node are given, together with the low-level video processing algorithms used, as well as the results obtained after their implementation...
Surveillance videos are often compressed for transmission or storage. It is desirable to be able to perform automatic event detection in the compressed domain directly. In this paper, we investigate the use of motion trajectories for video activity detection in the compressed domain. We show that it is possible to extract reliable motion trajectories directly from compressed H.264 video streams. To...
This paper presents a method, the snake particle filter (SPF), for tracking targets in video sequences. Manual or semi-automated solutions are both expensive and susceptible to error. In the SPF algorithm, automated tracking is accomplished by combining the particle filter with the snake. Here we employ the snake to establish the target shape, which is used to assign the weight for each particle in...
Unmanned Aircraft Systems (UAS) have been used in many military and civilian applications, particularly surveillance. One of the best ways to use the capacity of a UAS imaging system is by constructing a mosaic of the recorded video. In this paper, we present a novel algorithm to calculate a super-resolution mosaic for UAS, which is both fast and robust. In this algorithm, the features points between...
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