3D plant modelling via hyperspectral imaging
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Altmetric Citations
Liang, Jie; Zia, Ali; Zhou, Jun; Sirault, Xavier R. R.
Description
Plant phenomics research requires different types of sensors be employed to measure the physical traits of plant surface and to estimate the plant biomass. Of particular interest is the hyperspectral imaging device which captures wavelength indexed band images that characterise material properties of objects under study. In this paper, we introduce a proof of concept research that builds 3D plant model directly from hyperspectral images captured in a controlled lab environment. We show that...[Show more]
dc.contributor.author | Liang, Jie | |
---|---|---|
dc.contributor.author | Zia, Ali | |
dc.contributor.author | Zhou, Jun | |
dc.contributor.author | Sirault, Xavier R. R. | |
dc.coverage.spatial | Sydney Australia | |
dc.date.accessioned | 2015-12-10T23:07:45Z | |
dc.date.created | December 1-8 2013 | |
dc.identifier.isbn | 9781479930227 | |
dc.identifier.uri | http://hdl.handle.net/1885/63000 | |
dc.description.abstract | Plant phenomics research requires different types of sensors be employed to measure the physical traits of plant surface and to estimate the plant biomass. Of particular interest is the hyperspectral imaging device which captures wavelength indexed band images that characterise material properties of objects under study. In this paper, we introduce a proof of concept research that builds 3D plant model directly from hyperspectral images captured in a controlled lab environment. We show that hyperspectral imaging has shown clear advantages in segmenting plant from its background and is promising in generating comprehensive 3D plant models. | |
dc.publisher | IEEE | |
dc.relation.ispartofseries | 2013 14th IEEE International Conference on Computer Vision Workshops, ICCVW 2013 | |
dc.source | Proceedings of the IEEE International Conference on Computer Vision | |
dc.subject | Keywords: Spectroscopy; 3D plant modeling; Hyper-spectral images; Hyperspectral Imaging; Plant biomass; Plant model; Plant modelling; Plant surfaces; Proof of concept; Three dimensional | |
dc.title | 3D plant modelling via hyperspectral imaging | |
dc.type | Conference paper | |
local.description.notes | Imported from ARIES | |
local.description.refereed | Yes | |
dc.date.issued | 2013 | |
local.identifier.absfor | 080104 - Computer Vision | |
local.identifier.ariespublication | U3488905xPUB759 | |
local.type.status | Published Version | |
local.contributor.affiliation | Liang, Jie, College of Engineering and Computer Science, ANU | |
local.contributor.affiliation | Zia, Ali, Griffith University | |
local.contributor.affiliation | Zhou, Jun, Griffith University | |
local.contributor.affiliation | Sirault, Xavier R.R, CSIRO Plant Industry | |
local.description.embargo | 2037-12-31 | |
local.bibliographicCitation.startpage | 172 | |
local.bibliographicCitation.lastpage | 177 | |
local.identifier.doi | 10.1109/ICCVW.2013.29 | |
dc.date.updated | 2022-02-06T07:18:37Z | |
local.identifier.scopusID | 2-s2.0-84897482159 | |
local.identifier.thomsonID | 000349847200024 | |
Collections | ANU Research Publications |
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