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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
NIPS
2008
13 years 9 months ago
Local Gaussian Process Regression for Real Time Online Model Learning
Learning in real-time applications, e.g., online approximation of the inverse dynamics model for model-based robot control, requires fast online regression techniques. Inspired by...
Duy Nguyen-Tuong, Matthias Seeger, Jan Peters
NIPS
1994
13 years 9 months ago
Active Learning with Statistical Models
For many types of machine learning algorithms, one can compute the statistically optimal" way to select training data. In this paper, we review how optimal data selection tec...
David A. Cohn, Zoubin Ghahramani, Michael I. Jorda...
CAIP
2003
Springer
176views Image Analysis» more  CAIP 2003»
14 years 27 days ago
Evaluation of an Adaptive Composite Gaussian Model in Video Surveillance
Video surveillance systems seek to automatically identify events of interest in a variety of situations. Extracting a moving object from background is the most important step of t...
Qi Zang, Reinhard Klette
TASLP
2010
101views more  TASLP 2010»
13 years 2 months ago
Gaussian Model-Based Multichannel Speech Presence Probability
The knowledge of the target speech presence probability in a mixture of signals captured by a speech communication system is of paramount importance in several applications includi...
Mehrez Souden, Jingdong Chen, Jacob Benesty, Sofi&...