Filling missing parts of a 3D mesh by fusion of incomplete 3D data

Laszlo Kormoczi, Z. Kato

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper deals with the problem of fusing different (potentially partial) 3D meshes to fill in missing parts (holes) of an accurate reference 3D model using a less accurate but more complete moving 3D model. Typically, accurate 3D models can be produced by range devices (Lidar) which is often limited in setting viewpoints, while traditional Structure from Motion methods are using 2D images which are less restricted in viewpoints, but overall produce a less accurate 3D mesh. Combining the advantages of both modalities is an appealing solution to many real world problems. Herein we propose a novel method which detects holes in the accurate reference mesh and then each hole is filled from the less accurate 3D mesh by gradually estimating local affine transformations around the hole’s boundary and propagating it into the inner part. Experimental validation is done on a large real dataset, which confirms the accuracy and reliability of the proposed algorithm.

Original languageEnglish
Title of host publicationAdvanced Concepts for Intelligent Vision Systems - 18th International Conference, ACIVS 2017, Proceedings
PublisherSpringer Verlag
Pages711-722
Number of pages12
ISBN (Print)9783319703527
DOIs
Publication statusPublished - Jan 1 2017
Event18th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2017 - Antwerp, Belgium
Duration: Sep 18 2017Sep 21 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10617 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other18th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2017
CountryBelgium
CityAntwerp
Period9/18/179/21/17

Keywords

  • 3D registration
  • Hole filling
  • Lidar
  • Mesh fusion
  • Photogrammetry

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kormoczi, L., & Kato, Z. (2017). Filling missing parts of a 3D mesh by fusion of incomplete 3D data. In Advanced Concepts for Intelligent Vision Systems - 18th International Conference, ACIVS 2017, Proceedings (pp. 711-722). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10617 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-70353-4_60