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IBPRIA
2005
Springer
14 years 9 days ago
Monte Carlo Localization Using SIFT Features
The ability of finding its situation in a given environment is crucial for an autonomous agent. While navigating through a space, a mobile robot must be capable of finding its lo...
Arturo Gil, Óscar Reinoso, Maria Asunci&oac...
ICRA
2005
IEEE
167views Robotics» more  ICRA 2005»
14 years 11 days ago
Localization for Mobile Robots using Panoramic Vision, Local Features and Particle Filter
— In this paper we present a vision-based approach to self-localization that uses a novel scheme to integrate featurebased matching of panoramic images with Monte Carlo localizat...
Henrik Andreasson, André Treptow, Tom Ducke...
EUROS
2006
224views Robotics» more  EUROS 2006»
13 years 10 months ago
Metric Localization with Scale-Invariant Visual Features Using a Single Perspective Camera
Abstract. The Scale Invariant Feature Transform (SIFT) has become a popular feature extractor for vision-based applications. It has been successfully applied to metric localization...
Maren Bennewitz, Cyrill Stachniss, Wolfram Burgard...
ICPR
2008
IEEE
14 years 8 months ago
Local shape features for object recognition
We present a shape matching algorithm based on the chamfer distance transform which can be easily integrated into the well-known SIFT framework. The shape matching was designed to...
Bernd Heisele, Carlos Rocha
ICRA
2005
IEEE
149views Robotics» more  ICRA 2005»
14 years 11 days 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