Using phyllotaxis for date palm tree 3D reconstruction from a single image

Ran Dror, Ilan Shimshoni

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Phyllotaxis is the study of the morphological order of plants. Remarkably, in spite of the overwhelming diversity of plant morphology, there are common patterns that link a wide variety of species. The date palm, having a phyllotactic order, possesses a simple, repetitive model. Only a small number of parameters are needed to represent the phyllotactic order of the date palm. This a priori knowledge we have on the date palm can help in the 3D reconstruction of the tree and can even make it possible to reconstruct a 3D model from only one image. The proposed algorithm receives as input a single image of the date palm. Upon image acquisition, the algorithm proceeds to search for, and locate, the trunk followed by a few prominent leaves. From the location of the prominent leaves the algorithm proceeds to calculate tree model parameters, which can then be used to search for additional, neighboring, leaves. Complete 3D reconstruction is achieved by utilizing the calculated tree model parameters and by the known location of the leaves on the 2D image.

Original languageEnglish
Title of host publicationVISAPP 2009 - Proceedings of the 4th International Conference on Computer Vision Theory and Applications
Pages288-296
Number of pages9
StatePublished - 2009
Event4th International Conference on Computer Vision Theory and Applications, VISAPP 2009 - Lisboa, Portugal
Duration: 5 Feb 20098 Feb 2009

Publication series

NameVISAPP 2009 - Proceedings of the 4th International Conference on Computer Vision Theory and Applications
Volume2

Conference

Conference4th International Conference on Computer Vision Theory and Applications, VISAPP 2009
Country/TerritoryPortugal
CityLisboa
Period5/02/098/02/09

Keywords

  • 3D reconstruction
  • Palm tree
  • Phyllotaxis

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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