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ICASSP
2011
IEEE
13 years 2 months ago
Approximated kernel density estimation for multiple TDOA detection
The Generalized State Coherence Transform (GSCT) has been recently proposed as an efficient tool for the estimation of multidimensional TDOA of multiple sources. The transform de...
Francesco Nesta, Maurizio Omologo
PAMI
2010
146views more  PAMI 2010»
13 years 9 months ago
A Generalized Kernel Consensus-Based Robust Estimator
In this paper, we present a new Adaptive Scale Kernel Consensus (ASKC) robust estimator as a generalization of the popular and state-of-the-art robust estimators such as RANSAC (R...
Hanzi Wang, Daniel Mirota, Gregory D. Hager
CSDA
2008
94views more  CSDA 2008»
13 years 10 months ago
Feature significance for multivariate kernel density estimation
Multivariate kernel density estimation provides information about structure in data. Feature significance is a technique for deciding whether features
Tarn Duong, Arianna Cowling, Inge Koch, M. P. Wand
SIAMCO
2008
98views more  SIAMCO 2008»
13 years 10 months ago
Kernel Density Estimation and Goodness-of-Fit Test in Adaptive Tracking
We investigate the asymptotic properties of a recursive kernel density estimator associated with the driven noise of a linear regression in adaptive tracking. We provide an almost ...
Bernard Bercu, Bruno Portier
MLMTA
2007
14 years 10 days ago
Prediction of Protein Secondary Structures with a Novel Kernel Density Estimator
- Though prediction of protein secondary structures has been an active research issue in bioinformatics for quite a few years and many approaches have been proposed, a new challeng...
Yen-Jen Oyang, Darby Tien-Hao Chang, Yu-Yen Ou, Ha...
BCS
2008
14 years 11 days ago
Fast Estimation of Nonparametric Kernel Density Through PDDP, and its Application in Texture Synthesis
In this work, a new algorithm is proposed for fast estimation of nonparametric multivariate kernel density, based on principal direction divisive partitioning (PDDP) of the data s...
Arnab Sinha, Sumana Gupta
ICPR
2010
IEEE
14 years 4 months ago
Online Discriminative Kernel Density Estimation
—We propose a new method for online estimation of probabilistic discriminative models. The method is based on the recently proposed online Kernel Density Estimation (oKDE) framew...
Matej Kristan, Ales Leonardis
HUMO
2007
Springer
14 years 5 months ago
Nonparametric Density Estimation with Adaptive, Anisotropic Kernels for Human Motion Tracking
In this paper, we suggest to model priors on human motion by means of nonparametric kernel densities. Kernel densities avoid assumptions on the shape of the underlying distribution...
Thomas Brox, Bodo Rosenhahn, Daniel Cremers, Hans-...
IJCNN
2007
IEEE
14 years 5 months ago
Probability Density Function Estimation Using Orthogonal Forward Regression
— Using the classical Parzen window estimate as the target function, the kernel density estimation is formulated as a regression problem and the orthogonal forward regression tec...
Sheng Chen, Xia Hong, Chris J. Harris
IJCNN
2008
IEEE
14 years 5 months ago
Sparse kernel density estimator using orthogonal regression based on D-Optimality experimental design
— A novel sparse kernel density estimator is derived based on a regression approach, which selects a very small subset of significant kernels by means of the D-optimality experi...
Sheng Chen, Xia Hong, Chris J. Harris