Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
This paper proposes a background subtraction method for Bayer-pattern image sequences. The proposed method models the background in a Bayer-pattern domain using a mixture of Gauss...
Point Distribution Models are useful tools for modelling the variability of particular classes of shapes. A common approach is to apply a Principle Component Analysis to the data,...
James Orwell, Darrel Greenhill, Jonathan D. Rymel,...
This paper proposes an automatic foreground segmentation system based on Gaussian mixture models and dynamic graph cut algorithm. An adaptive perpixel background model is develope...
Inspired by the idea of multi-view, we proposed an image segmentation algorithm using co-EM strategy in this paper. Image data are modeled using Gaussian Mixture Model (GMM), and t...
Zhenglong Li, Jian Cheng, Qingshan Liu, Hanqing Lu