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» Feature Correspondence: A Markov Chain Monte Carlo Approach
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NIPS
2000
13 years 6 months ago
Feature Correspondence: A Markov Chain Monte Carlo Approach
When trying to recover 3D structure from a set of images, the most di cult problem is establishing the correspondence between the measurements. Most existing approaches assume tha...
Frank Dellaert, Steven M. Seitz, Sebastian Thrun, ...
ICRA
2005
IEEE
149views Robotics» more  ICRA 2005»
13 years 10 months ago
A Markov Chain Monte Carlo Approach to Closing the Loop in SLAM
— The problem of simultaneous localization and mapping has received much attention over the last years. Especially large scale environments, where the robot trajectory loops back...
Michael Kaess, Frank Dellaert
CVPR
2007
IEEE
13 years 11 months ago
Multiple Target Tracking Using Spatio-Temporal Markov Chain Monte Carlo Data Association
We propose a framework for general multiple target tracking, where the input is a set of candidate regions in each frame, as obtained from a state of the art background learning, ...
Qian Yu, Gérard G. Medioni, Isaac Cohen
KI
2010
Springer
13 years 3 months ago
Soft Evidential Update via Markov Chain Monte Carlo Inference
The key task in probabilistic reasoning is to appropriately update one’s beliefs as one obtains new information in the form of evidence. In many application settings, however, th...
Dominik Jain, Michael Beetz
ICCS
2007
Springer
13 years 11 months ago
Complexity of Monte Carlo Algorithms for a Class of Integral Equations
In this work we study the computational complexity of a class of grid Monte Carlo algorithms for integral equations. The idea of the algorithms consists in an approximation of the ...
Ivan Dimov, Rayna Georgieva