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Finite mixture models provide a natural way of modeling continuous or discrete outcomes that are observed from populations… Expand Background subtraction is a common computer vision task. We analyze the usual pixel-level approach. We develop an efficient… Expand Background subtraction is a common computer vision task. We analyze the usual pixel-level approach. We develop an efficient… Expand This paper proposes an unsupervised algorithm for learning a finite mixture model from multivariate data. The adjective… Expand The important role of finite mixture models in the statistical analysis of data is underscored by the ever-increasing rate at… Expand Reynolds, Douglas A., Quatieri, Thomas F., and Dunn, Robert B., Speaker Verification Using Adapted Gaussian Mixture Models… Expand A common method for real-time segmentation of moving regions in image sequences involves "background subtraction", or… Expand In a Bayesian mixture model it is not necessary a priori to limit the number of components to be finite. In this paper an… Expand This paper introduces and motivates the use of Gaussian mixture models (GMM) for robust text-independent speaker identification… Expand General Introduction Introduction History of Mixture Models Background to the General Classification Problem Mixture Likelihood… Expand