Improved Gaussian Mixture Models for Adaptive Foreground Segmentation

Abstract

Adaptive foreground segmentation is traditionally performed using Stauffer & Grimson’s algorithm that models every pixel of the frame by a mixture of Gaussian distributions with continuously adapted parameters. In this paper we provide an enhancement of the algorithm by adding two important dynamic elements to the baseline algorithm: The learning rate can… (More)
DOI: 10.1007/s11277-015-2628-3

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