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MVA
2002
195views Computer Vision» more  MVA 2002»
13 years 7 months ago
Improved Adaptive Mixture Learning for Robust Video Background Modeling
2 Related Works Gaussian mixtures are often used for data modeling in many real-time applications such as video background modeling and speaker direction tracking. The real-time a...
Dar-Shyang Lee
ICASSP
2010
IEEE
13 years 7 months ago
Robust background modeling via standard variance feature
In this paper, a novel standard variance feature is proposed for background modeling in dynamic scenes involving waving trees and ripples in water. The standard variance feature i...
Bineng Zhong, Hongxun Yao, Shaohui Liu
CVPR
2000
IEEE
13 years 12 months ago
Error Analysis of Background Adaption
Background modeling is a common component in video surveillance systems and is used to quickly identify regions of interest. To increase the robustness of background subtraction t...
Xiang Gao, Terrance E. Boult, Frans Coetzee, Visva...
ICPR
2008
IEEE
14 years 8 months ago
A covariance-based method for dynamic background subtraction
Background subtraction in dynamic scenes is an important and challenging task. In this paper, we present a novel and effective method for dynamic background subtraction based on c...
Hongxun Yao, Shaohui Liu, Shengping Zhang, Wen Gao...
CVPR
2012
IEEE
11 years 10 months ago
Background segmentation with feedback: The Pixel-Based Adaptive Segmenter
In this paper we present a novel method for foreground segmentation. Our proposed approach follows a nonparametric background modeling paradigm, thus the background is modeled by ...
Martin Hofmann 0011, Philipp Tiefenbacher, Gerhard...