Reconstruction of 3D models consisting of line segments

Naoto Ienaga, Hideo Saito

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

2 Citations (Scopus)


Reconstruction of three-dimensional (3D) models from images is currently one of the most important areas of research in computer vision. In this paper, we propose a method to recover 3D models using the minimum number of line segments. By using structure-from-motion, the proposed method first recovers a 3D model of line segments detected from an input image sequence. We then detect overlapping 3D line segments that redundantly represent a single line structure so that the number of 3D line segments representing the target scene can be reduced without losing the detailed geometry of the structure. We apply matching and depth information to remove redundant line segments from the model while keeping the necessary segments. In experiments, we confirm that the proposed method can greatly reduce the number of line segments. We also demonstrate that the accuracy and computational time for camera pose estimation can be significantly improved with the 3D line segment model recovered by the proposed method. Moreover, we have applied the proposed method to see through occluded areas.

Original languageEnglish
Title of host publicationComputer Vision - ACCV 2016 Workshops, ACCV 2016 International Workshops, Revised Selected Papers
EditorsKai-Kuang Ma, Jiwen Lu, Chu-Song Chen
PublisherSpringer Verlag
Number of pages14
ISBN (Print)9783319544267
Publication statusPublished - 2017
Event13th Asian Conference on Computer Vision, ACCV 2016 - Taipei, Taiwan, Province of China
Duration: 2016 Nov 202016 Nov 24

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10117 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other13th Asian Conference on Computer Vision, ACCV 2016
Country/TerritoryTaiwan, Province of China
City Taipei

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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