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On unifying key-frame and voxel-based dense visual SLAM at large scales

Abstract : This paper proposes an approach to real-time dense localisation and mapping that aims at unifying two different representations commonly used to define dense models. On one hand, much research has looked at 3D dense model representations using voxel grids in 3D. On the other hand, image-based key-frame representations for dense environment mapping have been developed. Both techniques have their relative advantages and disadvantages which will be analysed in this paper. In particular each representation's space-size requirements, their effective resolution, the computation efficiency, their accuracy and robustness will be compared. This paper then proposes a new model which unifies various concepts and exhibits the main advantages of each approach within a common framework. One of the main results of the proposed approach is its ability to perform large scale reconstruction accurately at the scale of mapping a building.
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Submitted on : Friday, March 8, 2019 - 3:05:40 PM
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Maxime Meilland, Andrew I. Comport. On unifying key-frame and voxel-based dense visual SLAM at large scales. International Conference on Intelligent Robots and Systems, 2013, Tokyo, Japan. ⟨10.1109/IROS.2013.6696881⟩. ⟨hal-01357359⟩



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