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AVSS
2006
IEEE
14 years 2 months ago
Feature Modelling of PCA Difference Vectors for 2D and 3D Face Recognition
This paper examines the the effectiveness of feature modelling to conduct 2D and 3D face recognition. In particular, PCA difference vectors are modelled using Gaussian Mixture Mod...
Chris McCool, Jamie Cook, Vinod Chandran, Sridha S...
ICASSP
2010
IEEE
13 years 8 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
ICASSP
2011
IEEE
12 years 12 months ago
Subspace pursuit method for kernel-log-linear models
This paper presents a novel method for reducing the dimensionality of kernel spaces. Recently, to maintain the convexity of training, loglinear models without mixtures have been u...
Yotaro Kubo, Simon Wiesler, Ralf Schlüter, He...
CVPR
2000
IEEE
14 years 18 days ago
Scene Modeling for Wide Area Surveillance and Image Synthesis
We present a method for modeling a scene that is observed by a moving camera, where only a portion of the scene is visible at any time. This method uses mixture models to represen...
Anurag Mittal, Daniel P. Huttenlocher
ICPR
2006
IEEE
14 years 9 months ago
A probabilistic model with parsinomious representation for sensor fusion in recognizing activity in pervasive environment
To tackle the problem of increasing numbers of state transition parameters when the number of sensors increases, we present a probabilistic model together with several parsinomiou...
Dinh Q. Phung, Dung T. Tran