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159
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CVPR
2005
IEEE
16 years 5 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
138
Voted
ICASSP
2010
IEEE
15 years 4 months ago
Image-quality prediction of synthetic aperture sonar imagery
This work exploits several machine-learning techniques to address the problem of image-quality prediction of synthetic aperture sonar (SAS) imagery. The objective is to predict th...
David P. Williams
129
Voted
ICASSP
2010
IEEE
15 years 4 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
ECCV
2008
Springer
16 years 5 months ago
Regular Texture Analysis as Statistical Model Selection
An approach to the analysis of images of regular texture is proposed in which lattice hypotheses are used to define statistical models. These models are then compared in terms of t...
Junwei Han, Stephen J. McKenna, Ruixuan Wang
123
Voted
ICASSP
2011
IEEE
14 years 7 months ago
Improving melody extraction using Probabilistic Latent Component Analysis
We propose a new approach for automatic melody extraction from polyphonic audio, based on Probabilistic Latent Component Analysis (PLCA). An audio signal is first divided into vo...
Jinyu Han, Ching-Wei Chen