Estimation of Branch Angle from 3D Point Cloud of Plants

Lu Lou, Yonghuai Liu, Minglan Shen, Jiwan Han, Fiona Corke, John H. Doonan

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

11 Citations (SciVal)

Abstract

Measuring geometric features in plant specimens either quantitatively or qualitatively, is crucial for plant phenotyping. However, traditional measurement methods tend to be manual and can be tedious, or employ coarse 2D imaging techniques. Emerging 3D imaging technologies show much promise in capturing architectural complexity. However, automated 3D acquisition and accurate estimation of plant morphology for the construction of quantitative plant models remain largely aspiration. In this paper, we propose an approach for segmentation and angle estimation directly from dense 3D plant point clouds. Experimental results show that the approach is efficient and reliable, and appears to be a promising 3D acquisition and measurement solution to plant phenotyping for structural analysis and for building Functional-Structural Plant Models (FSPM).
Original languageEnglish
Title of host publication2015 International Conference on 3D Vision (3DV)
EditorsMichael Brown, Jana Kosecka, Christian Theobolt
PublisherIEEE Press
Pages554-561
Number of pages8
ISBN (Electronic)978-1-4673-8332-5
ISBN (Print)978-1-4673-8331-8
DOIs
Publication statusPublished - Oct 2015
Event2015 International Conference on 3D Vision (3DV) - ENS, Lyon, France
Duration: 19 Oct 201522 Oct 2015

Conference

Conference2015 International Conference on 3D Vision (3DV)
Abbreviated title3DV2015
Country/TerritoryFrance
CityLyon
Period19 Oct 201522 Oct 2015

Keywords

  • 3D displays
  • solid modelling
  • skeleton
  • shape
  • image segmentation
  • image colour analysis
  • estimation

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