Monocular, real-time surface reconstruction using dynamic level of detail

Jacek Zienkiewicz, Akis Tsiotsios, Andrew Davison, Stefan Leutenegger

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

28 Scopus citations

Abstract

We present a scalable, real-time capable method for robust surface reconstruction that explicitly handles multiple scales. As a monocular camera browses a scene, our algorithm processes images as they arrive and incrementally builds a detailed surface model.While most of the existing reconstruction approaches rely on volumetric or point-cloud representations of the environment, we perform depth-map and colour fusion directly into a multi-resolution triangular mesh that can be adaptively tessellated using the concept of Dynamic Level of Detail. Our method relies on least-squares optimisation, which enables a probabilistically sound and principled formulation of the fusion algorithm.We demonstrate that our method is capable of obtaining high quality, close-up reconstruction, as well as capturing overall scene geometry, while being memory and computationally efficient.

Original languageEnglish
Title of host publicationProceedings - 2016 4th International Conference on 3D Vision, 3DV 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages37-46
Number of pages10
ISBN (Electronic)9781509054077
DOIs
StatePublished - 15 Dec 2016
Externally publishedYes
Event4th International Conference on 3D Vision, 3DV 2016 - Stanford, United States
Duration: 25 Oct 201628 Oct 2016

Publication series

NameProceedings - 2016 4th International Conference on 3D Vision, 3DV 2016

Conference

Conference4th International Conference on 3D Vision, 3DV 2016
Country/TerritoryUnited States
CityStanford
Period25/10/1628/10/16

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