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In this paper we propose multiple cameras using real time tracking for surveillance and security system. It is extensively used in the research field of computer vision applications, like that video surveillance, authentication systems, robotics, pre-stage of MPEG4 image compression and user inter faces by gestures. The key components of tracking for surveillance system are extracting the feature,...
Automatic traffic abnormality detection through visual surveillance is one of the critical requirements for Intelligent Transportation Systems (ITS). In this paper, we present a novel algorithm to detect abnormal traffic events in crowded scenes. Our algorithm can be deployed with few setup steps to automatically monitor traffic status. Different from other approaches, we don't need to define region...
In this paper, a quasi-automatic video matting approach which can preserve the temporal consistency of the alpha mattes is presented. “Quasi-automatic” means that it only needs a few user interactions on the first frame. A new algorithm which incorporates the Bayesian Estimation, Weighted Kernel Density Estimation (WKDE) and graph cut is presented to automatically and accurately segment each frame...
Color tone detection accomplishes the modelization of a color cluster for a set of pixels that present a hue similar to a particular one, which is being detected. Image pixels can be classified according to their membership to the particular color class through such cluster modelization. Such approaches can be employed in different computer vision application fields. Nevertheless few proposals in...
A real-time detection and tracking of moving objects in video sequences is very important for smart surveillance systems. However, due to dynamic changes in natural scenes such as sudden illumination and weather changes, repetitive motions that cause clutter, motion detection has been considered a difficult problem to process reliably. Hence, its robustness needs to be improved for applications in...
According to the result of moving object detection research on video sequences, this paper proposes a new method to detect moving object based on background subtraction. First of all, we establish a reliable background updating model based on statistical and use a dynamic optimization threshold method to obtain a more complete moving object. And then, morphological filtering is introduced to eliminate...
A correct video segmentation, namely the detection of moving objects within a scene plays a very important role in many application in safety, surveillance, traffic monitoring and object detection. The main objective of this paper is to implement an effective background segmentation algorithm for corner sets extracted from video sequences. A dynamic prototype of the structure of background corners...
In a ubiquitous network society, information on mobile nodes such as pedestrians with cell phones in a target region is useful for network configuration, communication control, and so on. In this paper, we propose a novel method to estimate in real time the number of pedestrians in video sequences using a stationary camera. The proposed method extracts moving regions from video frame grabs using background...
Considering the fact that High Definition (HD) becomes an important trend in road surveillance video, this paper studies vehicle location and license plate location methods in HD surveillance video. While license plate reading may obviously benefit from high definition technology, higher resolution also increases the computational load of graphical analysis and background interference. Most known...
Real time dynamic scene analysis has become very important aspect as the increase in video input analysis. Although several dynamic scene analysis techniques are available, some of them poses increased computational complexity problem. In the present work a simple differential algorithm is designed and tested with traffic flux estimation application. Traffic flux estimation will play a very vital...
This paper proposes a method of adaptive kernel density estimation (KDE) for motion detection. The method selects an adaptive threshold by analyzing probability histogram, which is suitable for different scenes and different moving objects. Then a mechanism of updating background using probability is also provided. It can get relative good background and is useful for motion detection. Moreover it...
This paper presents a very efficient method for extracting the non-linear summary of a video sequence by synthesizing new summary frames from a number of original frames. The non-linear summary of a video sequence is fundamentally different from the classical video summarizing techniques which discard full frames. The high efficiency of the method is due to the employment of dynamic programming to...
A real-time video segmentation algorithm, which can extract objects from video sequences even with non-stationary backgrounds, is proposed in this work. First, we segment the first frame into an object and a background interactively to build the probability density functions of colors in the object and the background. Then, for each subsequent frame, we construct a coherence strip, which is likely...
A shadow detection algorithm base on spatial features was proposed, in the case of focusing on traffic vehicle detection system. First of all, multi-foreground rectangles were extracted by using Gaussian mixture model (GMM) and edge detection operator of mathematical morphology. Then, histogram of horizontal location - foreground point number of vertical direction was computed, combined with optimum...
Foreground segmentation in videos by background subtraction methods are widely used in video surveillance applications. Adaptive single or mixture Gaussian models have been adopted for modeling nonstationary temporal distributions of background pixels. However, a challenge for this approach is that it is hard to choose a threshold to separate foreground from background accurately because of the so-called...
It is very challenging to de-interlace HD videos in real time, as both high efficiency and low complexity should be fulfilled, which, however, are conflicting. This paper presents a de-interlacer to resolve the conflict specially for H.264 coded videos. It adapts to spatially and temporally local activities by making full use of the syntax element (SE) values in bit-streams, which give many hints...
Visual analysis of human motion in video sequences has attached more and more attention to computer visions in recent years. In order to indicate pedestrian movement in Intelligent Monitoring System, a Euclidean distance based on centroid method is proposed. And then according to the movement of body a set of standard images contour are made. All matrixes which represent human silhouette are normalized...
In this paper we report a new method to detect both moving objects and new stationary objects in video sequences. On the basis of temporal consideration we classify pixels into three classes: background, midground and foreground to distinguish between long-term, medium-term and short term changes. The algorithm has been implemented on a hardware platform with limited resources and it could be used...
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