QR-code reconstruction from event data via optimization in code subspace

Jun Nagata, Yusuke Sekikawa, Kosuke Hara, Teppei Suzuki, Aoki Yoshimitsu

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

We propose an image reconstruction method from event data, assuming the target images belong to a prespecified class like QR codes. Instead of solving the reconstruction problem in the image space, we introduce a code space that covers all the noiseless target class images and solves the reconstruction problem on it. This restriction enormously reduces the number of optimizing parameters and makes the reconstruction problem well posed and robust to noise. We demonstrate fast and robust QR-code scanning in difficult, high-speed scenes with industrial high-speed cameras and other reconstruction methods.

本文言語English
ホスト出版物のタイトルProceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020
出版社Institute of Electrical and Electronics Engineers Inc.
ページ2113-2121
ページ数9
ISBN(電子版)9781728165530
DOI
出版ステータスPublished - 2020 3
イベント2020 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2020 - Snowmass Village, United States
継続期間: 2020 3 12020 3 5

出版物シリーズ

名前Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020

Conference

Conference2020 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2020
国/地域United States
CitySnowmass Village
Period20/3/120/3/5

ASJC Scopus subject areas

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

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引用スタイル