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» Monte Carlo Localization Using SIFT Features
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AAAI
2006
13 years 10 months ago
Bayesian Calibration for Monte Carlo Localization
Localization is a fundamental challenge for autonomous robotics. Although accurate and efficient techniques now exist for solving this problem, they require explicit probabilistic...
Armita Kaboli, Michael H. Bowling, Petr Musí...
ADHOC
2008
101views more  ADHOC 2008»
13 years 8 months ago
Monte Carlo localization for mobile wireless sensor networks
Localization is crucial to many applications in wireless sensor networks. In this article, we propose a range-free anchorbased localization algorithm for mobile wireless sensor ne...
Aline Baggio, Koen Langendoen
IROS
2006
IEEE
162views Robotics» more  IROS 2006»
14 years 2 months ago
Efficiency Improvement in Monte Carlo Localization through Topological Information
- Monte Carlo localization is known to be one of the most reliable methods for pose estimation of a mobile robot. Many studies have been conducted to improve performance of MCL. Al...
Tae-Bum Kwon, Ju-Ho Yang, Jae-Bok Song, Woojin Chu...
ICPR
2010
IEEE
13 years 8 months ago
A Discrete Labelling Approach to Attributed Graph Matching Using SIFT Features
Local invariant feature extraction methods are widely used for image-features matching. There exist a number of approaches aimed at the refinement of the matches between image-fe...
Gerard Sanromà, René Alquézar...
ICMCS
2008
IEEE
245views Multimedia» more  ICMCS 2008»
14 years 3 months ago
A novel local feature descriptor for image matching
Image matching is a fundamental task of many problems in computer vision. This paper presents a novel local feature descriptor based on the gradient distance and orientation histo...
Heng Yang, Qing Wang