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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 2015 International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2015
EditorsFatos Xhafa, Leonard Barolli
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages223-227
Number of pages5
ISBN (Electronic)9781467376945
DOIs
Publication statusPublished - Oct 28 2015
Externally publishedYes
Event7th International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2015 - Taipei, Taiwan, Province of China
Duration: Sept 2 2015Sept 4 2015

Publication series

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

Other

Other7th International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2015
Country/TerritoryTaiwan, Province of China
CityTaipei
Period9/2/159/4/15

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Artificial Intelligence

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