Name
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). |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/3DV.2015.68 | 3DV |
Keywords | Field | DocType |
branch angle estimation,geometric feature measurement,plant phenotyping,3D imaging technologies,architectural complexity,automated 3D acquisition,plant morphology,quantitative plant models,aspiration,segmentation process,dense-3D plant point clouds,functional-structural plant models,FSPM | Plant phenotyping,Computer vision,Segmentation,Computer science,Stereo display,Solid modelling,Image segmentation,Artificial intelligence,Solid modeling,Plant morphology,Point cloud | Conference |
Citations | PageRank | References |
0 | 0.34 | 19 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lu Lou | 1 | 3 | 0.74 |
| Yonghuai Liu | 2 | 675 | 61.65 |
| Minglan Sheng | 3 | 0 | 0.34 |
| Jiwan Han | 4 | 8 | 2.23 |
| Fiona Corke | 5 | 0 | 0.34 |
| John H. Doonan | 6 | 5 | 1.83 |