3D Multi-Tillering Crop Reconstruction Using Tiller Segmentation
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Solution Overview
Problem
Existing 3D reconstruction methods for multi-tillering crop plants with complex morphology and structure yield undesirable results due to numerous tillers, rich details, and cross-obscuration, leading to poor consistency with measured data.
Innovation Solution
A 3D reconstruction method involving point cloud data acquisition, determination of single-stem growth characteristics, use of a 3D leaf template database for leaf mesh models, and optimization of leaf azimuths to improve reconstruction accuracy and consistency with measured data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If deep learning method is used for 3D plant reconstruction based on point cloud, then reconstruction can be performed automatically, but reconstruction accuracy deteriorates for multi-tillering crops with complex structure
Solution Approach 1:
The patent segments the complex multi-tillering plant into multiple single-stem components for individual reconstruction. Each tiller is processed separately using the single-stem reconstruction algorithm, then the results are integrated. This segmentation approach allows the system to handle complex structures by breaking them down into manageable units that can be reconstructed with higher accuracy using automated methods.
2Ease of manufacture
If single-stem reconstruction method is used, then reconstruction process is simple, but it cannot handle multi-tillering crops with numerous tillers and cross-obscuration
Solution Approach 1:
The patent creates a universal reconstruction system that can handle both single-stem and multi-tillering crops. The core single-stem reconstruction algorithm is enhanced with tiller detection and segmentation capabilities, making it adaptable to various plant types. The system automatically determines whether to apply single-stem or multi-tillering reconstruction based on the input data characteristics.
3Ease of operation
If dispersed tillers are assumed for multi-tillering crop reconstruction, then reconstruction can proceed, but reconstruction result quality deteriorates for plants with complex morphology and rich details
Solution Approach 1:
The patent performs preliminary tiller segmentation and individual tiller reconstruction before integrating the complete plant model. By pre-processing the point cloud to identify and separate individual tillers, the system can apply optimized reconstruction algorithms to each tiller separately, preserving rich details and complex morphology that would be lost in a single-step reconstruction approach.
Data Source
AI summary
This application relates to the technical field of three-dimensional (3D) reconstruction, and in particular to a 3D reconstruction method and apparatus for a multi-tillering crop plant, a device, and a medium. The first reconstruction result of each single stem is obtained through the single-stem growth characteristic information and the 3D leaf template database, such that the 3D reconstruction result obtained based on the first reconstruction result exhibits satisfactory consistency with the measured data in crop phenotype. By optimizing the second reconstruction result, the optimized 3D reconstruction result exhibits satisfactory consistency with the measured data in vertical spatial distribution. This application can realize the 3D reconstruction for the multi-tillering crop plant of the complex morphology and structure, and provide a strong support for research of the multi-tillering crop plant.