Description: Gaussian mixture model, the classic English literature from 1997 to 2011, 13, very helpful with the students to learn the Gaussian model
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1997-Pfinder Real-time tracking of the human body(引用349).pdf
1999-stauffer_Adaptive background mixture models for real-time tracking（引用83）.pdf
2000-Learning Patterns of Activity Using Real-Time Tracking(引用480).pdf
2001-An Improved adaptive background mixture model for real-time tracking with shadow detection.pdf
2001-Multi-Object Tracking Using Dynamical Graph Matching.pdf
2002-Background and foreground modeling using nonparametric kernel density estimation for visual surveillance(引用201).pdf
2002-Understanding Background Mixture Models for Foreground Segmentation.pdf
2004-Improved adaptive Gaussian mixture model for background subtraction（引用28）.pdf
2004-Recursive Unsupervised Learning of Finite Mixture Models(引用32).pdf
2005-Effective gaussian mixture learning for video Background Subtraction（引用95）.pdf
2006-Efficient adaptive density estimation per image pixel for the task of background subtraction.pdf
2010-On the analysis of background subtraction techniques using Gaussian mixture models.pdf
2011-Regularized background Adaptation a novel learning rate control scheme for Gaussian mixture modeling.pdf
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