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Authors: Tawsif Gokhool 1 ; Maxime Meilland 2 ; Patrick Rives 1 and Eduardo Fernández-Moral 3

Affiliations: 1 INRIA, France ; 2 University of Nice Sophia Antipolis, France ; 3 Universidad de Málaga, Spain

ISBN: 978-989-758-009-3

Keyword(s): Visual Odometry, RGBD Dense Tracking, Spherical/Omnidirectional Vision, Optimisation, Pose Graph.

Related Ontology Subjects/Areas/Topics: Active and Robot Vision ; Applications ; Computer Vision, Visualization and Computer Graphics ; Image Formation and Preprocessing ; Image Formation, Acquisition Devices and Sensors ; Motion, Tracking and Stereo Vision ; Pattern Recognition ; Robotics ; Software Engineering ; Stereo Vision and Structure from Motion ; Tracking and Visual Navigation

Abstract: Visual mapping is a required capability for practical autonomous mobile robots where there exists a growing industry with applications ranging from the service to industrial sectors. Prior to map building, Visual Odometry(VO) is an essential step required in the process of pose graph construction. In this work, we first propose to tackle the pose estimation problem by using both photometric and geometric information in a direct RGBD image registration method. Secondly, the mapping problem is tackled with a pose graph representation, whereby, given a database of augmented visual spheres, a travelled trajectory with redundant information is pruned out to a skeletal pose graph. Both methods are evaluated with data acquired with a recently proposed omnidirectional RGBD sensor for indoor environments.

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Paper citation in several formats:
Gokhool, T.; Meilland, M.; Rives, P. and Fernández-Moral, E. (2014). A Dense Map Building Approach from Spherical RGBD Images.In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-009-3, pages 656-663. DOI: 10.5220/0004745406560663

@conference{visapp14,
author={Tawsif Gokhool. and Maxime Meilland. and Patrick Rives. and Eduardo Fernández{-}Moral.},
title={A Dense Map Building Approach from Spherical RGBD Images},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={656-663},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004745406560663},
isbn={978-989-758-009-3},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)
TI - A Dense Map Building Approach from Spherical RGBD Images
SN - 978-989-758-009-3
AU - Gokhool, T.
AU - Meilland, M.
AU - Rives, P.
AU - Fernández-Moral, E.
PY - 2014
SP - 656
EP - 663
DO - 10.5220/0004745406560663

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