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ISDA
2010
IEEE
13 years 4 months ago
Self-adaptive Gaussian mixture models for real-time video segmentation and background subtraction
The usage of Gaussian mixture models for video segmentation has been widely adopted. However, the main difficulty arises in choosing the best model complexity. High complex models ...
Nicola Greggio, Alexandre Bernardino, Cecilia Lasc...
CVPR
1999
IEEE
1071views Computer Vision» more  CVPR 1999»
14 years 9 months ago
Adaptive Background Mixture Models for Real-Time Tracking
A common method for real-time segmentation of moving regions in image sequences involves "background subtraction," or thresholding the error between an estimate of the i...
Chris Stauffer, W. Eric L. Grimson
CAIP
2007
Springer
217views Image Analysis» more  CAIP 2007»
14 years 1 months ago
Mixture Models Based Background Subtraction for Video Surveillance Applications
— Background subtraction is a method commonly used to segment objects of interest in image sequences. By comparing new frames to a background model, regions of interest can be fo...
Chris Poppe, Gaëtan Martens, Peter Lambert, R...
CVPR
2005
IEEE
14 years 9 months ago
Robust and Efficient Foreground Analysis for Real-Time Video Surveillance
We present a new method to robustly and efficiently analyze foreground when we detect background for a fixed camera view by using mixture of Gaussians models and multiple cues. Th...
Ying-li Tian, Max Lu, Arun Hampapur
ICIP
2003
IEEE
14 years 9 months ago
A Bayesian framework for Gaussian mixture background modeling
Background subtraction is an essential processing component for many video applications. However, its development has largely been application driven and done in ad hoc manners. I...
Dar-Shyang Lee, Jonathan J. Hull, Berna Erol