A Fundamental Study on Coded Aperture Design for Depth from Projector Defocus Based on Evolutionary Multi-objective Optimization

Yudai Mido, Yuki Horita, Kentaro Nakai, Taishi Megano, Satoshi Ono, Hiroshi Kawasaki

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

1 被引用数 (Scopus)

抄録

It is a reasonable idea to solve a problem whose property has not been clarified yet using evolutionary multiobjective optimization (EMO) because EMO does not require domain specific knowledge and analysis for obtained pareto solution set may reveal relationships between design variables and objective functions. This paper focuses on designing a coded aperture (CA), one of the hot topics in computer photography; CA is used in a camera or a projector for deblurring, constructing all-focus image, depth estimation and so on. Since little knowledge has been accumulated for designing CA, this paper proposes a CA design method using EMO. Experiments on designing projector aperture have shown relationships between the performance of depth estimation, aperture ratio, and noise robustness.

本文言語英語
ホスト出版物のタイトルProceedings - 2015 International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2015
編集者Fatos Xhafa, Leonard Barolli
出版社Institute of Electrical and Electronics Engineers Inc.
ページ223-227
ページ数5
ISBN(電子版)9781467376945
DOI
出版ステータス出版済み - 10 28 2015
外部発表はい
イベント7th International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2015 - Taipei, 台湾省、中華民国
継続期間: 9 2 20159 4 2015

出版物シリーズ

名前Proceedings - 2015 International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2015

その他

その他7th International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2015
国/地域台湾省、中華民国
CityTaipei
Period9/2/159/4/15

All Science Journal Classification (ASJC) codes

  • コンピュータ ネットワークおよび通信
  • コンピュータ サイエンスの応用
  • ハードウェアとアーキテクチャ
  • 人工知能

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