3D plant modelling via hyperspectral imaging

Jie Liang; Ali Zia; Jun Zhou; Xavier Sirault

doi:10.1109/ICCVW.2013.29

3D plant modelling via hyperspectral imaging

Jie Liang, Ali Zia, Jun Zhou, Xavier Sirault

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

27 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings - 2013 IEEE International Conference on Computer Vision Workshops, ICCVW 2013
Place of Publication	Sydney, NSW
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	172-177
Number of pages	6
Edition	Peer Reviewed
ISBN (Print)	9781479930227
DOIs	https://doi.org/10.1109/ICCVW.2013.29 https://doi.org/10.1109/ICCVW.2013.29
Publication status	Published - 2013
Event	2013 14th IEEE International Conference on Computer Vision Workshops, ICCVW 2013 - Sydney, NSW, Australia Duration: 1 Dec 2013 → 8 Dec 2013

Publication series

Name	Proceedings of the IEEE International Conference on Computer Vision

Conference

Conference	2013 14th IEEE International Conference on Computer Vision Workshops, ICCVW 2013
Country/Territory	Australia
City	Sydney, NSW
Period	1/12/13 → 8/12/13

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Liang, J., Zia, A., Zhou, J., & Sirault, X. (2013). 3D plant modelling via hyperspectral imaging. In Proceedings - 2013 IEEE International Conference on Computer Vision Workshops, ICCVW 2013 (Peer Reviewed ed., pp. 172-177). Article 6755894 (Proceedings of the IEEE International Conference on Computer Vision). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCVW.2013.29, https://doi.org/10.1109/ICCVW.2013.29

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title = "3D plant modelling via hyperspectral imaging",

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.",

author = "Jie Liang and Ali Zia and Jun Zhou and Xavier Sirault",

year = "2013",

doi = "10.1109/ICCVW.2013.29",

language = "English",

isbn = "9781479930227",

series = "Proceedings of the IEEE International Conference on Computer Vision",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "172--177",

booktitle = "Proceedings - 2013 IEEE International Conference on Computer Vision Workshops, ICCVW 2013",

address = "United States",

edition = "Peer Reviewed",

note = "2013 14th IEEE International Conference on Computer Vision Workshops, ICCVW 2013 ; Conference date: 01-12-2013 Through 08-12-2013",

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Liang, J, Zia, A, Zhou, J & Sirault, X 2013, 3D plant modelling via hyperspectral imaging. in Proceedings - 2013 IEEE International Conference on Computer Vision Workshops, ICCVW 2013. Peer Reviewed edn, 6755894, Proceedings of the IEEE International Conference on Computer Vision, Institute of Electrical and Electronics Engineers Inc., Sydney, NSW, pp. 172-177, 2013 14th IEEE International Conference on Computer Vision Workshops, ICCVW 2013, Sydney, NSW, Australia, 1/12/13. https://doi.org/10.1109/ICCVW.2013.29, https://doi.org/10.1109/ICCVW.2013.29

3D plant modelling via hyperspectral imaging. / Liang, Jie; Zia, Ali; Zhou, Jun et al.
Proceedings - 2013 IEEE International Conference on Computer Vision Workshops, ICCVW 2013. Peer Reviewed. ed. Sydney, NSW: Institute of Electrical and Electronics Engineers Inc., 2013. p. 172-177 6755894 (Proceedings of the IEEE International Conference on Computer Vision).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Zhou, Jun

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AB - 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.

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M3 - Conference contribution

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BT - Proceedings - 2013 IEEE International Conference on Computer Vision Workshops, ICCVW 2013

PB - Institute of Electrical and Electronics Engineers Inc.

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T2 - 2013 14th IEEE International Conference on Computer Vision Workshops, ICCVW 2013

Y2 - 1 December 2013 through 8 December 2013

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Liang J, Zia A, Zhou J, Sirault X. 3D plant modelling via hyperspectral imaging. In Proceedings - 2013 IEEE International Conference on Computer Vision Workshops, ICCVW 2013. Peer Reviewed ed. Sydney, NSW: Institute of Electrical and Electronics Engineers Inc. 2013. p. 172-177. 6755894. (Proceedings of the IEEE International Conference on Computer Vision). doi: 10.1109/ICCVW.2013.29, 10.1109/ICCVW.2013.29

3D plant modelling via hyperspectral imaging

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