Learning Visibility of Landmarks for Vision-Based Localization

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1853/38323

Title: Learning Visibility of Landmarks for Vision-Based Localization
Author: Alcantarilla, Pablo F. ; Oh, Sang Min ; Mariottini, Gian Luca ; Bergasa, Luis M. ; Dellaert, Frank
Abstract: We aim to perform robust and fast vision-based localization using a pre-existing large map of the scene. A key step in localization is associating the features extracted from the image with the map elements at the current location. Although the problem of data association has greatly benefited from recent advances in appearance-based matching methods, less attention has been paid to the effective use of the geometric relations between the 3D map and the camera in the matching process. In this paper we propose to exploit the geometric relationship between the 3D map and the camera pose to determine the visibility of the features. In our approach, we model the visibility of every map feature w.r.t. the camera pose using a non-parametric distribution model. We learn these non-parametric distributions during the 3D reconstruction process, and develop efficient algorithms to predict the visibility of features during localization. With this approach, the matching process only uses those map features with the highest visibility score, yielding a much faster algorithm and superior localization results. We demonstrate an integrated system based on the proposed idea and highlight its potential benefits for the localization in large and cluttered environments.
Description: ©2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Presented at the 2010 IEEE International Conference on Robotics and Automation (ICRA), 3-7 May 2010, Anchorage, AK. DOI: 10.1109/ROBOT.2010.5509383
Type: Post-print
URI: http://hdl.handle.net/1853/38323
ISSN: 1050-4729
Citation: Alcantarilla, P.F., Oh, S. M., Mariottini, G.L., Bergasa, L.M., Dellaert, F.(2010). “Learning Visibility of Landmarks for Vision-Based Localization”. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2010), 3-7 May 2010, 4881-4888.
Date: 2010
Contributor: Georgia Institute of Technology. Center for Robotics and Intelligent Machines
Georgia Institute of Technology. College of Computing
Georgia Institute of Technology. School of Interactive Computing
Universidad de Alcalá. Departamento de Electrónica
University of Minnesota. Dept. of Computer Science and Engineering
Publisher: Georgia Institute of Technology
Institute of Electrical and Electronics Engineers
Subject: Camera pose
Data association
3D landmark
3D maps

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