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CVPR
2012
IEEE
13 years 9 months ago
Background modeling using adaptive pixelwise kernel variances in a hybrid feature space
Recent work on background subtraction has shown developments on two major fronts. In one, there has been increasing sophistication of probabilistic models, from mixtures of Gaussi...
Manjunath Narayana, Allen R. Hanson, Erik G. Learn...
ICPR
2004
IEEE
16 years 7 months ago
Visual Learning and Recognition of a Probabilistic Spatio-Temporal Model of Cyclic Human Locomotion
We present a novel representation of cyclic human locomotion based on a set of spatio-temporal curves of tracked points on the surface of a person. We start by extracting a set of...
Miha Peternel, Ales Leonardis
ICML
2009
IEEE
16 years 7 months ago
Matrix updates for perceptron training of continuous density hidden Markov models
In this paper, we investigate a simple, mistakedriven learning algorithm for discriminative training of continuous density hidden Markov models (CD-HMMs). Most CD-HMMs for automat...
Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul
ISBI
2008
IEEE
16 years 7 months ago
Improved fMRI group studies based on spatially varying non-parametric BOLD signal modeling
Multi-subject analysis of functional Magnetic Resonance Imaging (fMRI) data relies on within-subject studies, which are usually conducted using a massively univariate approach. In...
Philippe Ciuciu, Thomas Vincent, Anne-Laure Fouque...
CADE
2007
Springer
16 years 7 months ago
Combination Methods for Satisfiability and Model-Checking of Infinite-State Systems
Manna and Pnueli have extensively shown how a mixture of first-order logic (FOL) and discrete Linear time Temporal Logic (LTL) is sufficient to precisely state verification problem...
Silvio Ghilardi, Enrica Nicolini, Silvio Ranise, D...