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Fast Dynamic Control of Adaptive Mixture-of-Gaussian Background Models
Atsushi SHIMADA Daisaku ARITA Rin-ichiro TANIGUCHI
D - Abstracts of IEICE TRANSACTIONS on Information and Systems (Japanese Edition)
Publication Date: 2007/09/01
Online ISSN: 1881-0225
Print ISSN: 1880-4535
Type of Manuscript: PAPER
background subtraction, object detection, adaptive background model, Gaussian mixture,
Full Text(in Japanese): PDF(1.2MB)
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We propose a method for create a background model in non-stationary scenes. Each pixel has a Gaussian mixture model, and it is updated as a function of a variation of pixel values. Our approach can automatically change the number of Gaussians in each pixel. The number of Gaussians increases when pixel values often change because of Illumination change, object moving and so on. On the other hand, when pixel values are constant in a while, some Gaussians are eliminated or integrated. This process helps reduce computational time. We conducted experiments to investigate the effectiveness of our approach.