ArticleSensors (Basel, Switzerland)2019
Low-Cost Three-Dimensional Modeling of Crop Plants.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Phenotypic analysis method for 3D reconstruction of eggplant seedlings fused with background purification - based on the improved EggplantPointNet++ model and DBSCAN clustering.Frontiers in plant science · 2026Article
- Phenological growth stages of Finger millet (Frontiers in plant science · 2026Article
- Implementation of an SfM-MVS-based photogrammetry approach for detailed 3D reconstruction of plants.Plant methods · 2025Article
- Investigation of salt stress effects on maize seedling phenotypic traits based on the PointCornNet point cloud segmentation model.Frontiers in plant science · 2025Article
- How to make sense of 3D representations for plant phenotyping: a compendium of processing and analysis techniques.Plant methods · 2023Review
- Dynamic detection of three-dimensional crop phenotypes based on a consumer-grade RGB-D camera.Frontiers in plant science · 2023Article
- Extraction of soybean plant trait parameters based on SfM-MVS algorithm combined with GRNN.Frontiers in plant science · 2023Article
- Point cloud registration method for maize plants based on conical surface fitting-ICP.Scientific reports · 2022Article
- Three-dimensional reconstruction and phenotype measurement of maize seedlings based on multi-view image sequences.Frontiers in plant science · 2022Article
- Enhancing the Tracking of Seedling Growth Using RGB-Depth Fusion and Deep Learning.Sensors (Basel, Switzerland) · 2021Article
- Open source 3D phenotyping of chickpea plant architecture across plant development.Plant methods · 2021Article
- A Low-Cost 3D Phenotype Measurement Method of Leafy Vegetables Using Video Recordings from Smartphones.Sensors (Basel, Switzerland) · 2020Article
- A Rapid Method of the Rock Mass Surface Reconstruction for Surface Deformation Detection at Close Range.Sensors (Basel, Switzerland) · 2020Article
- Performances Evaluation of a Low-Cost Platform for High-Resolution Plant Phenotyping.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Plant modeling can provide a more detailed overview regarding the basis of plant development throughout the life cycle. Three-dimensional processing algorithms are rapidly expanding in plant phenotyping programmes and in decision-making for agronomic management. Several methods have already been tested, but for practical implementations the trade-off between equipment cost, computational resources needed and the fidelity and accuracy in the reconstruction of the end-details needs to be assessed and quantified. This study examined the suitability of two low-cost systems for plant reconstruction. A low-cost Structure from Motion (SfM) technique was used to create 3D models for plant crop reconstruction. In the second method, an acquisition and reconstruction algorithm using an RGB-Depth Kinect v2 sensor was tested following a similar image acquisition procedure. The information was processed to create a dense point cloud, which allowed the creation of a 3D-polygon mesh representing every scanned plant. The selected crop plants corresponded to three different crops (maize, sugar beet and sunflower) that have structural and biological differences. The parameters measured from the model were validated with ground truth data of plant height, leaf area index and plant dry biomass using regression methods. The results showed strong consistency with good correlations between the calculated values in the models and the ground truth information. Although, the values obtained were always accurately estimated, differences between the methods and among the crops were found. The SfM method showed a slightly better result with regard to the reconstruction the end-details and the accuracy of the height estimation. Although the use of the processing algorithm is relatively fast, the use of RGB-D information is faster during the creation of the 3D models. Thus, both methods demonstrated robust results and provided great potential for use in both for indoor and outdoor scenarios. Consequently, these low-cost systems for 3D modeling are suitable for several situations where there is a need for model generation and also provide a favourable time-cost relationship.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.