3D植物表型分析的转折点：3D基础模型实现分钟到秒级的跨作物重建及更多
The Turning Point of 3D Plant Phenotyping: 3D Foundation Models Enable Minute-to-Second Cross-Crop Reconstruction and Beyond
AI总结：
提出基于3D基础模型的跨作物表型分析框架，用前馈几何恢复替代COLMAP，结合3D高斯泼溅实现少视图重建，将重建时间从6.52分钟降至1.58秒，保持高质量与高精度。
摘要：
3D植物表型分析因多视图成像繁琐、重建流程脆弱以及从重建几何到表型提取的额外成本而著称，流程复杂且通量低。这些限制在低成本数据采集中进一步放大，智能手机视频或稀疏采样的多视图图像仅提供有限的视图重叠和自遮挡。在这项工作中，我们展示了传统的3D植物表型分析流程可以通过3D基础模型（3DFMs）得到简化和显著加速，并特别提出了首个由3DFM驱动的跨作物3D表型分析框架。该框架用基于3DFM的前馈几何恢复替代COLMAP风格的稀疏初始化，结合几何约束的3D高斯泼溅进行密集重建，通过迭代视图合成与细化实现少视图重建，并通过2D到3D语义迁移、度量尺度恢复和器官实例分割将重建几何转换为可测量的器官。我们进一步构建了一个跨作物数据集，包含基于智能手机的图像采集、多样的植物形态以及用于分割和表型评估的人工标注。在26个植物序列上的实验表明，3D基础模型将平均重建时间从6.52分钟减少到1.58秒，同时保持高重建质量和表型精度。这些结果为高通量3D植物表型分析提供了一条新的技术路线，从低成本图像采集到快速重建、感知、尺度恢复和表型测量。
英文摘要：
3D plant phenotyping is notoriously known to be procedure-complicated and of low throughput due to the extensive multi-view imaging, the fragile 3D reconstruction pipeline, and the additional cost from reconstructed geometry to phenotypic extraction. These limitations are further amplified in low-cost data acquisition, where smartphone videos or sparsely sampled multi-view images provide limited view overlap and self-occlusion. In this work, we show that the conventional 3D plant phenotyping pipeline could be streamlined and significantly accelerated with 3D Foundation Models (3DFMs), and particularly, present one of the first cross-crop 3D phenotyping frameworks powered by 3DFMs. The framework replaces COLMAP-style sparse initialization with 3DFM-based feed-forward geometric recovery, combines geometry-constrained 3D Gaussian Splatting for dense reconstruction, enables few-view reconstruction through iterative view synthesis and refinement, and converts reconstructed geometry into measurable organs through 2D-to-3D semantic transfer, metric scale recovery, and organ instance separation. We further construct a cross-crop dataset with smartphone-based image acquisition, diverse plant morphologies, and manual annotations for segmentation and phenotypic evaluation. Experiments across 26 plant sequences show that 3D Foundation Models reduce the average reconstruction time from 6.52 minutes to 1.58 seconds while maintaining high reconstruction quality and phenotyping accuracy. These results suggest a fresh technical route for high-throughput 3D plant phenotyping, from low-cost image acquisition to fast reconstruction, perception, scale recovery, and phenotypic measurement.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
