Applicaton of ViBe Algorithm for People Counting in a crowded Environment

Minu. S, Dr.V.Cyril Raj


People counting is a very important problem in visual surveillance. An accurate and real time estimation of people in a crowded place can provide valuable information. Here video is given as input and outputs the average number of people passing over the video. The video input is separated to number of frames and some processing steps are performed on background subtraction results to estimate the number of people in a complicated scene. Foreground pixel extraction is done with ViBe (VIsual Background Extractor) algorithm. The extracted foreground image’s pixels count is calculated and gives as input to the neural network. In learning phase, the people count is calculated manually with test dataset and while testing phase remaining test cases are tested by adjusting weight parameters to obtain relative to the target result.

Keywords: background subtraction, ViBe (VIsual Background Extractor) algorithm, neural network, and people counting.

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