Photometric Estimation

Katsushi Ikeuchi, Yasuyuki Matsushita, Ryusuke Sagawa, Hiroshi Kawasaki, Yasuhiro Mukaigawa, Ryo Furukawa, Daisuke Miyazaki

研究成果: 書籍/レポート タイプへの寄稿

抄録

Previous chapters considered methods of estimating geometric shape information by using active-lighting methods, which provide photometric characteristics of the target scene and light sources. Because BRDF depends on materials, adequate lighting and analysis provides rich information about those materials. Moreover, multispectral light gives us more robust identification capability. Furthermore, polarization and fluorescence are useful for material classification. Analyzing captured images enables us to separate an image into several photometric components. Additionally, a scene illuminated by multiple lights can be decomposed into an image illuminated by a single light. As such, active lighting is useful, not only for geometrical analysis, but also for photometrical analysis.

本文言語英語
ホスト出版物のタイトルAdvances in Computer Vision and Pattern Recognition
出版社Springer Science and Business Media Deutschland GmbH
ページ183-209
ページ数27
DOI
出版ステータス出版済み - 2020

出版物シリーズ

名前Advances in Computer Vision and Pattern Recognition
ISSN(印刷版)2191-6586
ISSN(電子版)2191-6594

!!!All Science Journal Classification (ASJC) codes

  • ソフトウェア
  • 信号処理
  • コンピュータ ビジョンおよびパターン認識
  • 人工知能

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