Accurate Multi-View Stereo 3D Reconstruction for Cost-Effective Plant Phenotyping

Lu Lou, Yonghuai Liu, Jiwan Han, John H. Doonan

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

28 Citations (SciVal)

Abstract

Phenotyping, which underpins much of plant biology and breeding, involves the measurement of characteristics or traits. Traditionally, this has been often destructive and/or subjective but the dynamic objective measurement of traits as they change in response to genetic mutation or environmental influences is an important goal. 3-D imaging technologies are increasingly incorporated into mass produced consumer goods (3D laser scanning, structured light and digital photography) and may represent a cost-effective alternative to current commercial phenotyping platforms. We evaluate their performance, cost and practicability for plant phenotyping and present a 3D reconstruction method for plants from multi-view images acquired with domestic quality cameras. We exploit an efficient Structure-From-Motion followed by stereo matching and depth-map merging processes. Experimental results show that the proposed method is flexible, adaptable and inexpensive, and promising as an generalized groundwork for phenotyping various plant species.
Original languageEnglish
Title of host publicationImage Analysis and Recognition
Subtitle of host publication11th International Conference, ICIAR 2014, Vilamoura, Portugal, October 22-24, 2014, Proceedings, Part II
EditorsAurélio Campilho, Mohamed Kamel
PublisherSpringer Nature
Pages349-356
Number of pages8
ISBN (Electronic)978-3-319-11755-3
ISBN (Print)978-3-319-11754-6, 3319117548
DOIs
Publication statusPublished - 10 Oct 2014

Publication series

NameLecture Notes in Computer Science
Volume8815
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • plant phenotyping
  • multi-view images
  • Structure from Motion (SfM)
  • stereovision
  • 3D reconstruction

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