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ICRA
2008
IEEE
134views Robotics» more  ICRA 2008»
15 years 4 months ago
An optimal filtering algorithm for non-parametric observation models in robot localization
— The lack of a parameterized observation model in robot localization using occupancy grids requires the application of sampling-based methods, or particle filters. This work ad...
Jose-Luis Blanco, Javier Gonzalez, Juan-Antonio Fe...
96
Voted
IROS
2008
IEEE
211views Robotics» more  IROS 2008»
15 years 4 months ago
GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models
Abstract— Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. The most common instantiations of Bayes filters are Kalman filt...
Jonathan Ko, Dieter Fox
ICIP
2005
IEEE
15 years 11 months ago
Non-parametric image super-resolution using multiple images
In this paper, we present a novel learning based framework for performing super-resolution using multiple images. We model the image as an undirected graphical model over image pa...
Mithun Das Gupta, ShyamSundar Rajaram, Nemanja Pet...
NIPS
2007
14 years 11 months ago
Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms
The peristimulus time histogram (PSTH) and its more continuous cousin, the spike density function (SDF) are staples in the analytic toolkit of neurophysiologists. The former is us...
Dominik Endres, Mike W. Oram, Johannes E. Schindel...
ICASSP
2011
IEEE
14 years 1 months ago
Motion vector recovery with Gaussian Process Regression
In this paper, we propose a Gaussian Process Regression (GPR) framework for concealment of corrupted motion vectors in predictive video coding of packet video systems. The problem...
Hadi Asheri, Abdolkhalegh Bayati, Hamid R. Rabiee,...