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» Monte Carlo Localization Using SIFT Features
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ICML
2006
IEEE
15 years 10 months ago
A choice model with infinitely many latent features
Elimination by aspects (EBA) is a probabilistic choice model describing how humans decide between several options. The options from which the choice is made are characterized by b...
Carl Edward Rasmussen, Dilan Görür, Fran...
81
Voted
3DPVT
2006
IEEE
171views Visualization» more  3DPVT 2006»
15 years 3 months ago
Image Based Localization in Urban Environments
In this paper we present a prototype system for image based localization in urban environments. Given a database of views of city street scenes tagged by GPS locations, the system...
Wei Zhang, Jana Kosecka
84
Voted
ICRA
2008
IEEE
182views Robotics» more  ICRA 2008»
15 years 4 months ago
Hybrid laser and vision based object search and localization
— We describe a method for an autonomous robot to efficiently locate one or more distinct objects in a realistic environment using monocular vision. We demonstrate how to effic...
Dorian Galvez Lopez, Kristoffer Sjöö, Ch...
77
Voted
ICRA
2002
IEEE
100views Robotics» more  ICRA 2002»
15 years 2 months ago
Preliminary Results in Range-Only Localization and Mapping
This paper presents methods of localization using cooperating landmarks (beacons) that provide the ability to measure range only. Recent advances in radio frequency technology mak...
George Kantor, Sanjiv Singh
65
Voted
NIPS
2007
14 years 11 months ago
Feature Selection Methods for Improving Protein Structure Prediction with Rosetta
Rosetta is one of the leading algorithms for protein structure prediction today. It is a Monte Carlo energy minimization method requiring many random restarts to find structures ...
Ben Blum, Michael I. Jordan, David Kim, Rhiju Das,...