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» Distributed adaptive sampling using bounded-errors
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ACCV
2009
Springer
13 years 8 months ago
Adaptive-Scale Robust Estimator Using Distribution Model Fitting
We propose a new robust estimator for parameter estimation in highly noisy data with multiple structures and without prior information on the noise scale of inliers. This is a diag...
Trung Ngo Thanh, Hajime Nagahara, Ryusuke Sagawa, ...
ICPR
2008
IEEE
14 years 8 months ago
An adaptive Monte Carlo approach to nonlinear image denoising
This paper introduces a novel stochastic approach to image denoising using an adaptive Monte Carlo scheme. Random samples are generated from the image field using a spatially-adap...
Alexander Wong, Akshaya Kumar Mishra, Paul W. Fieg...
ICRA
2008
IEEE
143views Robotics» more  ICRA 2008»
14 years 2 months ago
Adaptive workspace biasing for sampling-based planners
Abstract— The widespread success of sampling-based planning algorithms stems from their ability to rapidly discover the connectivity of a configuration space. Past research has ...
Matthew Zucker, James Kuffner, James A. Bagnell
SIGGRAPH
1994
ACM
13 years 11 months ago
Using particles to sample and control implicit surfaces
We present a new particle-based approach to sampling and controlling implicit surfaces. A simple constraint locks a set of particles onto a surface while the particles and the sur...
Andrew P. Witkin, Paul S. Heckbert
SIGMOD
2004
ACM
150views Database» more  SIGMOD 2004»
14 years 7 months ago
When one Sample is not Enough: Improving Text Database Selection Using Shrinkage
Database selection is an important step when searching over large numbers of distributed text databases. The database selection task relies on statistical summaries of the databas...
Panagiotis G. Ipeirotis, Luis Gravano