Automated recovery of 3D models of plant shoots from multiple colour images
Increased adoption of the systems approach to biological research has focussed attention on the use of quantitative models of biological objects. This includes a need for realistic 3D representations of plant shoots for quantification and modelling. Previous limitations in single or multi-view stere...
| Main Authors: | , , , |
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| Format: | Article |
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American Society of Plant Biologists
2014
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| Online Access: | https://eprints.nottingham.ac.uk/29219/ |
| _version_ | 1848793740429230080 |
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| author | Pound, Michael P. French, Andrew P. Murchie, Erik H. Pridmore, Tony P. |
| author_facet | Pound, Michael P. French, Andrew P. Murchie, Erik H. Pridmore, Tony P. |
| author_sort | Pound, Michael P. |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Increased adoption of the systems approach to biological research has focussed attention on the use of quantitative models of biological objects. This includes a need for realistic 3D representations of plant shoots for quantification and modelling. Previous limitations in single or multi-view stereo algorithms have led to a reliance on volumetric methods or expensive hardware to record plant structure. We present a fully automatic approach to image-based 3D plant reconstruction that can be achieved using a single low-cost camera. The reconstructed plants are represented as a series of small planar sections that together model the more complex architecture of the leaf surfaces. The boundary of each leaf patch is refined using the level set method, optimising the model based on image information, curvature constraints and the position of neighbouring surfaces. The reconstruction process makes few assumptions about the nature of the plant material being reconstructed, and as such is applicable to a wide variety of plant species and topologies, and can be extended to canopy-scale imaging. We demonstrate the effectiveness of our approach on datasets of wheat and rice plants, as well as a novel virtual dataset that allows us to compute quantitative measures of reconstruction accuracy. The output is a 3D mesh structure that is suitable for modelling applications, in a format that can be imported in the majority of 3D graphics and software packages. |
| first_indexed | 2025-11-14T19:05:06Z |
| format | Article |
| id | nottingham-29219 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:05:06Z |
| publishDate | 2014 |
| publisher | American Society of Plant Biologists |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-292192020-05-04T20:13:15Z https://eprints.nottingham.ac.uk/29219/ Automated recovery of 3D models of plant shoots from multiple colour images Pound, Michael P. French, Andrew P. Murchie, Erik H. Pridmore, Tony P. Increased adoption of the systems approach to biological research has focussed attention on the use of quantitative models of biological objects. This includes a need for realistic 3D representations of plant shoots for quantification and modelling. Previous limitations in single or multi-view stereo algorithms have led to a reliance on volumetric methods or expensive hardware to record plant structure. We present a fully automatic approach to image-based 3D plant reconstruction that can be achieved using a single low-cost camera. The reconstructed plants are represented as a series of small planar sections that together model the more complex architecture of the leaf surfaces. The boundary of each leaf patch is refined using the level set method, optimising the model based on image information, curvature constraints and the position of neighbouring surfaces. The reconstruction process makes few assumptions about the nature of the plant material being reconstructed, and as such is applicable to a wide variety of plant species and topologies, and can be extended to canopy-scale imaging. We demonstrate the effectiveness of our approach on datasets of wheat and rice plants, as well as a novel virtual dataset that allows us to compute quantitative measures of reconstruction accuracy. The output is a 3D mesh structure that is suitable for modelling applications, in a format that can be imported in the majority of 3D graphics and software packages. American Society of Plant Biologists 2014-10 Article PeerReviewed Pound, Michael P., French, Andrew P., Murchie, Erik H. and Pridmore, Tony P. (2014) Automated recovery of 3D models of plant shoots from multiple colour images. Plant Physiology, 166 (4). pp. 1688-1698. ISSN 0032-0889 http://www.plantphysiol.org/content/166/4/1688.full doi:10.1104/pp.114.248971 doi:10.1104/pp.114.248971 |
| spellingShingle | Pound, Michael P. French, Andrew P. Murchie, Erik H. Pridmore, Tony P. Automated recovery of 3D models of plant shoots from multiple colour images |
| title | Automated recovery of 3D models of plant shoots from multiple colour images |
| title_full | Automated recovery of 3D models of plant shoots from multiple colour images |
| title_fullStr | Automated recovery of 3D models of plant shoots from multiple colour images |
| title_full_unstemmed | Automated recovery of 3D models of plant shoots from multiple colour images |
| title_short | Automated recovery of 3D models of plant shoots from multiple colour images |
| title_sort | automated recovery of 3d models of plant shoots from multiple colour images |
| url | https://eprints.nottingham.ac.uk/29219/ https://eprints.nottingham.ac.uk/29219/ https://eprints.nottingham.ac.uk/29219/ |