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» Monte Carlo Localization Using SIFT Features
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ACG
2006
Springer
15 years 3 months ago
Solving Probabilistic Combinatorial Games
Probabilistic combinatorial games (PCG) are a model for Go-like games recently introduced by Ken Chen. They differ from normal combinatorial games since terminal position in each ...
Ling Zhao, Martin Müller 0003
HUC
2009
Springer
15 years 2 months ago
Simultaneous localization and mapping for pedestrians using only foot-mounted inertial sensors
In this paper we describe a new Bayesian estimation approach for simultaneous mapping and localization for pedestrians based on odometry with foot mounted inertial sensors. When s...
Patrick Robertson, Michael Angermann, Bernhard Kra...
CVPR
2007
IEEE
15 years 11 months ago
Metropolis-Hasting techniques for finite-element-based registration
In this paper, we focus on the design of Markov Chain Monte Carlo techniques in a statistical registration framework based on finite element basis (FE). Due to the use of FE basis...
Adeline M. M. Samson, Frédéric J. P....
AAAI
2006
14 years 11 months ago
Probabilistic Self-Localization for Sensor Networks
This paper describes a technique for the probabilistic self-localization of a sensor network based on noisy inter-sensor range data. Our method is based on a number of parallel in...
Dimitri Marinakis, Gregory Dudek
CVPR
2007
IEEE
15 years 11 months ago
Learning Local Image Descriptors
In this paper we study interest point descriptors for image matching and 3D reconstruction. We examine the building blocks of descriptor algorithms and evaluate numerous combinati...
Simon A. J. Winder, Matthew Brown