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Detection of moving objects in video streams is the first relevant step of information extraction in many computer vision applications. Aside from the intrinsic usefulness of being able to segment video streams into moving and background components, detecting moving objects provides a focus of attention for recognition, classification, and activity analysis, making these later steps more efficient...
This paper presents a background modeling algorithm and a foreground detecting method which is robust against illumination change, providing a novel and practical choice for intelligent video surveillance systems using static cameras. This paper first introduces an online Expectation Maximization algorithm which is developed from the basic batch edition to update the mixture models in real time. Then...
The improved moving object detection and shadow removing algorithms for video surveillance are presented in this paper. The proposed algorithm processes two foregrounds performed by improved GMM and chromaticity-gradient background subtraction methods. The proposed algorithm improves the classic Gaussian Mixture Model to remove some unfavorable influences, such as sudden and gradual illumination changes,...
The concept of active tracking is presented to simulate the characteristics of human vision in intelligent visual surveillance. The Pan/Tilt/Zoom (PTZ) camera is generally used for active tracking. In this paper, we present a novel and effective approach for active object tracking with a PTZ camera, and construct a near real-time system for indoor and outdoor scenes. The tracking algorithm of our...
Motion analysis can be applied in a number of fields including, e.g. video surveillance, human-computer interaction, smart homes, etc. Due to the large amounts of data associated with usual videos, it is essential for motion analysis algorithms to be computationally efficient. In view of the remarkable efficiency of biological vision systems in dealing with visual information, we propose a motion...
Conventional surveillance systems present video to a user from more than one camera on a single display. Such a display allows the user to observe different part of the scene, or the same part of the scene from different viewpoints. With the growing number of surveillance cameras set up and the expanse of surveillance area, the conventional split-screen display approach cannot provide intuitive correspondence...
In this paper we implement a vision based moving Object Tracking system with Wireless Surveillance Camera which uses a color image segmentation and color histogram with background subtraction for tracking any objects in non-ideal environment. The implementation of the moving video objects can be based on any one of the tracking algorithms such as Template matching, Continuously Adaptive Mean Shift...
Video surveillance is proposed in the paper. The three key features of abnormal behavior are represented by energy. In which the velocity of the moving target is reflected by optical flow, and the disorder feature of the motion is expressed by entropy. For the last feature, energy is used to express the relative positions of the moving targets. The experiments show the good effects of the method in...
Detection and classification of vehicles are the most challenging tasks of a video-based intelligent transportation system. Traditional detection and classification methods are based on subtraction of estimated still backgrounds from a video to find out the moving objects. In general, these methods are computationally highly expensive, and in many cases show poor detection and classification performance,...
This paper proposes an automatic vehicles counting, classification and tracking for identifying Traffic flows in an intersection which is a fundamental task for video surveillance in urban traffic management. In intelligent transportation systems (ITS), especially in field of urban traffic management, intersections monitoring is one of the critical and challenging tasks. Where, objects have different...
The background identification methods are used in many fields like video surveillance and traffic monitoring. In this paper we propose a hardware implementation of the Gaussian Mixture Model algorithm able to perform background identification on HD images. The proposed circuit is based on the OpenCV implementation, particularly suited to improve the initial background learning phase. Bit-width has...
In panoramic videos, the object movement between adjacent side images leads to deformation and discontinuity, which makes the traditional video tracking approaches insufficient. An effective static object tracking algorithm is proposed in this paper to resolve the tracking problems from the deformation and discontinuity in cubic panorama. The algorithm extends the relevant side images with boundary...
This paper arose out of a need for marking surveillance video in a simple manner that would allow the integrity of that video against later manipulation to be assured from the camera to the court room. We present a novel use of a video watermarking system. The system is based on an array construction method using seed sequences that allows a simple hardware-generated watermark to be inserted into...
The ability to measure metric information from videos is an essential functionality in security software packages that populate databases with human morphometric and gait descriptors. The configuration of such security systems often involves calibrating the cameras in the surveillance network. For this purpose, markers are placed on the ground in the vicinity of each camera location in order to compute...
In this paper, we propose a computationally efficient fall detection algorithm which exploits visual observations. The proposed architecture is designed to be suitable for devices of low processing capabilities allowing a large scale implementation of the proposed IT technology in the area of aiding elderly or persons' with dementia. In contrast to other approaches, visual surveillance is more natural...
Traditional level-set-based methods of tracking contours suffered from occlusion and fusion. In this paper, the proposed method introduces dynamic incident detection to find and handle occlusion and fusion. Color histogram of the hue component in HSV color space is used to identify the objects re-entering after occlusion. On the other hand, object features including the size and the motion pattern...
We present a system to perform video analysis in the context of traffic surveillance's application. A training step is performed to estimate the scene's geometry and global information about the motion that occurs in the scene. Lanes boundaries, depth and motion information given by the initialization step are used to assist the vehicles' segmentation and to correct eventual errors.
Shadow detection is a critical issue for most applications of video surveillance. In this study, we present an object-wise online learning method to detect casting shadows without providing any priori scene information or threshold parameters. Hue, saturation, and intensity- difference histograms of moving objects are collected to learn a cumulative distribution separately. The accumulating strategy...
This paper presents an intelligent video surveillance system. The system is composed of one or more nodes flexibly according to the application scenarios such as private properties, banks and museums. Each node is an autonomous vision-based device capable to perform intelligent tasks. It is able to digitize and compress the acquired analog video signals in MPEG-4 standard and then transmit the compressed...
When facing the emergencies, to achieve the whole day real-time scanning services on targets, we propose a program with integration of visible and infrared imagers. A novel airborne low-altitude monitoring system is designed. it helps operators to detect targets accurately. Experiments show that the design is feasible and the system is practical, reliable, and easy to operate, displays Chinese characters,...
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