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基于改进的鱼类重建,计算猪点云的体积
Junyong Lin1, Hongyu Chen1, Runkang Wu1
1College of Mathematics and Informatics, South China Agricultural University, Guangzhou 510642, China.
Animals : an open access journal from MDPI
|April 27, 2024
概括
这项研究引入了对猪点云的改进的Poisson重建算法,使猪体重的准确估计和用于繁殖的新型表型分析成为可能. 该方法增强了畜牧管理的数字重建.
科学领域:
- 农业工程 农业工程
- 计算机视觉 计算机视觉
- 动物科学动物科学
背景情况:
- 猪点云数据为数字重建和重量估计提供了潜力.
- 猪点云中的不规则形状和缺失的数据阻碍了准确的体积计算.
- 使用身体部位比例的新型表型分析可以帮助选择性繁殖.
研究的目的:
- 为猪点云开发和验证一个改进的Poisson重建算法.
- 准确计算猪体体积和估计体重.
- 探索体积衍生的表型在养猪中的实用性.
主要方法:
- 一个改进的Poisson重建算法被应用于猪体点云.
- 标准形状的点云,子模型,小猪模型和479个猪数据集用于验证.
- 使用重建的点云进行体积计算和体重估计.
主要成果:
- 改进的Poisson重建产生了更光滑,更连续,更完整的猪体模型.
- 小猪模型的体积计算显示了4%的相对误差.
- 根据体积估计的重量平均绝对误差为2.664公斤,相对误差为2.478%.
- 在猪体体积和体重之间发现了0.95的高相关系数.
结论:
- 改进的Poisson重建算法对于猪点云分析是准确和可靠的.
- 猪体积是体重的强有力的预测指标,相关性很高.
- 这种方法为估计牲畜体重和开发用于育种计划的新表型提供了有价值的工具.
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