Single-wavelength and multi-parallel dotted- A nd solid-lines for dense and robust active 3D reconstruction

Genki Nagamatsu, Ryo Furukawa, Ryusuke Sagawa, Hiroshi Kawasaki

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

1 被引用数 (Scopus)

抄録

A dense one-shot scanning technique that is robust to subsurface scattering is proposed. In this technique, a novel pattern, consisting of multiple parallel dotted lines and solid lines, that are aligned alternately, is proposed. To project such a pattern efficiently, a single-wavelength laser-based pattern projector is developed. To detect patterns robustly from captured images, a black and white camera attached with a narrow-band-path filter is used in conjunction with our novel deep learning based algorithm, which is based on a convolutional neural network (CNN). Because the detected lines must be identified for shape reconstruction, we apply a gap-coding technique, which is originally based on a grid-line pattern, to the dot pattern. To this end, we introduce a virtual grid-line structure, which is generated from the dot pattern. Additionally, we propose a calibration algorithm specialized for our system, where the pattern is static and shared with the shape reconstruction algorithm, i. e., correspondence problem remains. For a solution, gap-coding is further applied to find correspondences under epipolar constraints. The experimental results of scanning real objects are presented to demonstrate the effectiveness of our calibration and reconstruction techniques.

本文言語英語
ホスト出版物のタイトルProceedings of the 16th International Conference on Machine Vision Applications, MVA 2019
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9784901122184
DOI
出版ステータス出版済み - 5月 2019
イベント16th International Conference on Machine Vision Applications, MVA 2019 - Tokyo, 日本
継続期間: 5月 27 20195月 31 2019

出版物シリーズ

名前Proceedings of the 16th International Conference on Machine Vision Applications, MVA 2019

会議

会議16th International Conference on Machine Vision Applications, MVA 2019
国/地域日本
CityTokyo
Period5/27/195/31/19

!!!All Science Journal Classification (ASJC) codes

  • コンピュータ サイエンスの応用
  • 信号処理
  • コンピュータ ビジョンおよびパターン認識

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