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Foreground detection is the classical computer vision task of segmenting out motion information from a particular scene. Foreground detection using Gaussian Mixture Models (GMM) is the famous choice. Since first time proposed, many researchers tried to improve GMM. This paper focuses on the comparative evaluation of three most famous improvements in the algorithm. The improved methods are compared...
Fire detection system in the surveillance system monitors the indoor environment and issues alarm as part of the early warning mechanism with ultimate goal to provide an alarm at early stage before the fire become uncontrollable. Conventional fire detection systems suffer from the transparent delay from the fire to the sensor which is looking at a point. The reliability of the fire detection system...
This paper is concerned with the detection of moving objects using a pan-tilt camera and a background subtraction algorithm. Traditionally, motion compensation is performed on the current image to align its pixels with their background models in previous frames. Pixel misalignment however can occur during motion compensation. Although this problem can be alleviated by using pixel motion such as the...
We address the problem of moving object detection in aerial video. Moving object detection in aerial video is still a challenging problem for the reason that when capturing the video the camera (or the platform) is moving all the time. As a result, the problem is detecting moving object from moving background which is much more difficult than the case that the background is constant. To this end,...
In this work, we propose a novel method for detection of moving or static objects which are not part of the background in an image sequence captured by a moving camera. The method is composed of two stages, namely, construction of a background model and detection of occluding objects. The constructed background model makes it possible to detect both static and moving occluding objects. Experiments...
In this paper, we present a novel approach for constructing an adaptive panoramic and multi-layered background model for Pan-tilt-zoom (PTZ) camera that provides fast registration of the observed frame and localizes the foreground targets with arbitrary camera position and scale (optical zoom). Our method consists of two stages. (1) An adaptive panoramic background mixture model is generated off-line...
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