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This paper presents a very good approach for tracking through occlusion by applying a probabilistic model to tracking features on an object. The authors present that the method works well even through partial occlusions.
Gaussian mixture models (GMM) is used to represent the dynamic background in a surveillance video to detect the moving objects automatically. All the existing GMM based techniques inherently use the proportion by which a pixel is going to observe the background in any operating environment. In this paper we first show that such a proportion not only varies widely across different scenarios but also...
The focus of the paper is on establishing the mapping between a fixed camera and the PTZ camera using master-slave configuration. The authors proposed and developed a general framework for arbitrary camera topology. The method estimates online the time-variant transformation between a fixed master camera having global view and tracking the target and a slave camera taking close up images. In the experiment,...
The paper describes a general platform for live video analysis. The first stage of the platform is to build a topological scene description by learning the location of nodes (i.e. zones), which are called points of interest. There are two kinds of points of interest, the entry-exit zones (areas where moving object appear and disappear in the scene) and the stopping zones (areas where the moving objects...
Processing a video stream to segment foreground objects from the background is a critical first step in many computer vision applications. Background subtraction (BGS) is a commonly used technique for achieving this segmentation. The popularity of BGS largely comes from its computational efficiency, which allows applications such as human-computer interaction, video surveillance, and traffic monitoring...
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