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ICCV
2005
IEEE
13 years 10 months ago
KALMANSAC: Robust Filtering by Consensus
We propose an algorithm to perform causal inference of the state of a dynamical model when the measurements are corrupted by outliers. While the optimal (maximumlikelihood) soluti...
Andrea Vedaldi, Hailin Jin, Paolo Favaro, Stefano ...
CORR
2010
Springer
189views Education» more  CORR 2010»
13 years 3 months ago
Robust PCA via Outlier Pursuit
Singular Value Decomposition (and Principal Component Analysis) is one of the most widely used techniques for dimensionality reduction: successful and efficiently computable, it ...
Huan Xu, Constantine Caramanis, Sujay Sanghavi
ICIP
2007
IEEE
14 years 6 months ago
Robust Image Segmentation with Mixtures of Student's t-Distributions
Gaussian mixture models have been widely used in image segmentation. However, such models are sensitive to outliers. In this paper, we consider a robust model for image segmentati...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. Ga...
CDC
2008
IEEE
130views Control Systems» more  CDC 2008»
13 years 11 months ago
Stochastic multiscale approaches to consensus problems
Abstract— While peer-to-peer consensus algorithms have enviable robustness and locality for distributed estimation and computation problems, they have poor scaling behavior with ...
Jong-Han Kim, Matthew West, Sanjay Lall, Eelco Sch...
JSAC
2008
143views more  JSAC 2008»
13 years 4 months ago
Distributed Kalman filtering based on consensus strategies
In this paper, we consider the problem of estimating the state of a dynamical system from distributed noisy measurements. Each agent constructs a local estimate based on its own m...
Ruggero Carli, Alessandro Chiuso, Luca Schenato, S...