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» Background Subtraction Based on a Robust Consensus Method
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PAMI
2010
146views more  PAMI 2010»
13 years 5 months ago
A Generalized Kernel Consensus-Based Robust Estimator
In this paper, we present a new Adaptive Scale Kernel Consensus (ASKC) robust estimator as a generalization of the popular and state-of-the-art robust estimators such as RANSAC (R...
Hanzi Wang, Daniel Mirota, Gregory D. Hager
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
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
PCM
2005
Springer
117views Multimedia» more  PCM 2005»
14 years 25 days ago
A Robust Text Segmentation Approach in Complex Background Based on Multiple Constraints
In this paper we propose a robust text segmentation method in complex background. The proposed method first utilizes the K-means algorithm to decompose a detected text block into ...
Libo Fu, Weiqiang Wang, Yaowen Zhan
DPHOTO
2009
189views Hardware» more  DPHOTO 2009»
13 years 5 months ago
Automatic background generation from a sequence of images based on robust mode estimation
In this paper, we present a novel method for generating a background model from a sequence of images with moving objects. Our approach is based on non-parametric statistics and ro...
Desire Sidibé, Olivier Strauss, William Pue...