Reconstruction of 3D models consisting of line segments

Naoto Ienaga, Hideo Saito

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルComputer Vision - ACCV 2016 Workshops, ACCV 2016 International Workshops, Revised Selected Papers
出版社Springer Verlag
ページ100-113
ページ数14
10117 LNCS
ISBN(印刷版)9783319544267
DOI
出版ステータスPublished - 2017
イベント13th Asian Conference on Computer Vision, ACCV 2016 - Taipei, Taiwan, Province of China
継続期間: 2016 11 202016 11 24

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
10117 LNCS
ISSN(印刷版)03029743
ISSN(電子版)16113349

Other

Other13th Asian Conference on Computer Vision, ACCV 2016
CountryTaiwan, Province of China
City Taipei
Period16/11/2016/11/24

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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