An Easy-to-Setup 3D Phenotyping Platform for KOMATSUNA Dataset

Hideaki Uchiyama, Shunsuke Sakurai, Masashi Mishima, Daisaku Arita, Takashi Okayasu, Atsushi Shimada, Rin Ichiro Taniguchi

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

14 Citations (Scopus)

Abstract

We present a 3D phenotyping platform that measures both plant growth and environmental information in small indoor environments for plant image datasets. Our objective is to construct a compact and complete platform by using commercial devices to allow any researcher to begin plant phenotyping in their laboratory. In addition, we introduce our annotation tool to manually but effectively create leaf labels in plant images on a pixel-by-pixel basis. Finally, we show our RGB-D and multiview datasets containing images in the early growth stages of the Komatsuna with leaf annotation.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2038-2045
Number of pages8
ISBN (Electronic)9781538610343
DOIs
Publication statusPublished - Jul 1 2017
Event16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017 - Venice, Italy
Duration: Oct 22 2017Oct 29 2017

Publication series

NameProceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017
Volume2018-January

Other

Other16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017
CountryItaly
CityVenice
Period10/22/1710/29/17

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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