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» Robust background modeling via standard variance feature
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ACCV
2010
Springer
13 years 2 months ago
MRF-Based Background Initialisation for Improved Foreground Detection in Cluttered Surveillance Videos
Abstract. Robust foreground object segmentation via background modelling is a difficult problem in cluttered environments, where obtaining a clear view of the background to model i...
Vikas Reddy, Conrad Sanderson, Andres Sanin, Brian...
ICML
2009
IEEE
14 years 8 months ago
Robust bounds for classification via selective sampling
We introduce a new algorithm for binary classification in the selective sampling protocol. Our algorithm uses Regularized Least Squares (RLS) as base classifier, and for this reas...
Nicolò Cesa-Bianchi, Claudio Gentile, Franc...
ICIP
2009
IEEE
13 years 5 months ago
Object tracking by bidirectional learning with feature selection
This paper proposes a new tracking algorithm which combines object and background information, via building object and background appearance models simultaneously by nonparametric...
Heng Wang, Xinwen Hou, Cheng-Lin Liu
AAAI
2012
11 years 10 months ago
Discriminative Clustering via Generative Feature Mapping
Existing clustering methods can be roughly classified into two categories: generative and discriminative approaches. Generative clustering aims to explain the data and thus is ad...
Liwei Wang, Xiong Li, Zhuowen Tu, Jiaya Jia
BELL
2000
107views more  BELL 2000»
13 years 7 months ago
Automating software feature verification
A significant part of the call processing software for Lucent's new PathStar access server [FSW98] was checked with automated formal verification techniques. The verification...
Gerard J. Holzmann, Margaret H. Smith