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Meilland12a

M. Meilland, P. Rives, A. I. Comport. Dense RGB-D mapping of large scale environments for real-time localisation and autonomous navigation. In Intelligent Vehicle (IV'12) Workshop on Navigation, Perception, Accurate Positioning and Mapping for Intelligent Vehicles, Alcala de Henares, Spain, June 2012.

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Abstract

This paper presents a method and apparatus for building 3D dense visual maps of large scale environments for real-time localisation and autonomous navigation. We propose a spherical ego-centric representation of the environment which is able to reproduce photo-realistic omnidirectional views of captured environments. This representation is composed of a graph of locally accurate augmented spherical panoramas that allows to generate varying viewpoints through novel view synthesis. The spheres are related by a graph of 6 d.o.f. poses which are estimated through multi-view spherical registration. It is shown that this representation can be used to accurately localise a vehicle navigating within the spherical graph, using only a monocular camera for accurate localisation. To perform this task, an efficient direct image registration technique is employed. This approach directly exploits the advantages of the spherical representation by minimising a photometric error between a current image and a reference sphere. Autonomous navigation results are shown in challenging urban environ- ments, containing pedestrians and other vehicles

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Patrick Rives

BibTex Reference

@InProceedings{Meilland12a,
   Author = {Meilland, M. and Rives, P. and I. Comport, A.},
   Title = {Dense RGB-D mapping of large scale environments for real-time localisation and autonomous navigation},
   BookTitle = {Intelligent Vehicle (IV'12) Workshop on Navigation, Perception, Accurate Positioning and Mapping for Intelligent Vehicles},
   Address = {Alcala de Henares, Spain},
   Month = {June},
   Year = {2012}
}

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