Description

Abandoned Object Detection

               In this project object detection is an essential requirement in many video surveillance contexts.we propose a method to detect abandoned object from surveillance video. Different from conventional approaches that mostly rely on pixellevel processing, we perform region-level analysis in both background maintenance and static foreground object detection. In background maintenance, region-level information is fed back to adaptively control the learning rate. In static foreground object detection, region-level analysis double-checks the validity of candidate abandoned blobs. Different from conventional approaches that mostly rely on pixel-level processing, we perform region-level analysis. In this project, we present an abandoned object detection system based on blob detection methods are aimed at detecting regions. In a digital image that differs in properties, such as brightness or color, compared to surrounding regions. Informally, a blob is a region of an image in which some properties are constant or approximately constant. All the points in a blob can be considered in some sense to be similar to each other

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