Model-Based MVS point reconstruction of texture-less regions with epipolar constraints

Yuichiro Yamaguchi, Masafumi Nakagawa

研究成果: Conference contribution

抄録

ABSTRUCT: Point clouds are acquired with Structure from Motion/Multi-View Stereo (SfM/MVS) and laser scanning for Building Information Modeling (BIM). Although the SfM/MVS can generate dense point clouds, it is not easy to reconstruct texture-less regions because the SfM/MVS is based on feature-based image matching. Thus, in metal bridge measurements, point clouds are not generated in many texture-less regions such as the plane of the girder. Therefore, we propose a model-based MVS methodology with epipolar constraints using the intrinsic parameters and extrinsic parameters estimated with SfM processing. Our point cloud reconstruction approach consists of SfM, texture-less region selection with sparse point cloud back-projection, and dense point cloud generation with model-based MVS. We selected metal bridge girders as measured objects. Through our experiment, we confirmed that our methodology can reconstruct point clouds, even if measured regions are texture-less.

本文言語English
ホスト出版物のタイトルACRS 2020 - 41st Asian Conference on Remote Sensing
出版社Asian Association on Remote Sensing
ISBN(電子版)9781713829089
出版ステータスPublished - 2020
イベント41st Asian Conference on Remote Sensing, ACRS 2020 - Deqing City, Virtual, China
継続期間: 2020 11 92020 11 11

出版物シリーズ

名前ACRS 2020 - 41st Asian Conference on Remote Sensing

Conference

Conference41st Asian Conference on Remote Sensing, ACRS 2020
国/地域China
CityDeqing City, Virtual
Period20/11/920/11/11

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信

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