Precise 3D Reconstruction of Plants from UAV Imagery Combining Bundle Adjustment and Template Matching
Precise 3D Reconstruction of Plants from UAV Imagery Combining Bundle Adjustment and Template Matching
复制标题
结合捆绑调整和模板匹配，利用无人机图像精确 3D 重建植物
DOI：
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
C. Stachniss
中科院分区：
文献类型：
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作者：
E. Marks;Federico Magistri;C. Stachniss
监测单个植物并计算精确的3D重建对于作物育种来说是高度相关的。在传统的育种方法中，人类需要手工测量表型特征，这需要大量的体力劳动。本文研究了基于无人机图像的农田或养殖场中植物的精确三维重建。我们明确地解决了由叶子的薄结构和自然发生的自闭塞所产生的挑战。我们将摄影测量束平差与基于模板的匹配方法相结合，生成准确的3D模型，使我们能够推导出育种者用于表型植物的常见几何性状。我们对商业使用的甜菜育种小区进行了全面的实验评估，以说明我们方法的能力以及它在现实世界中的适用性。
Monitoring individual plants and computing precise 3D reconstructions is highly relevant for crop breeding. In the conventional breeding approach, humans measure phenotypic traits by hand, requiring substantial manual labor. This paper addresses precise 3D plant reconstructions in a crop field or breeding plot based on UAV imagery. We explicitly address the challenges resulting from the thin structures of leaves and naturally occurring self-occlusions. We combine photogrammetric bundle adjustment with a template-based matching approach and produce accurate 3D models that allow us to derive common, geometric traits used by breeders to phenotype plants. We provide a thorough experimental evaluation on commercially used sugar beet breeding plots to illustrate the capabilities of our method as well as its real world applicability.
影响因子：
3.5
作者：
Hornung, Armin;Wurm, Kai M.;Burgard, Wolfram
通讯作者：
Burgard, Wolfram