Comparison of open‐source three‐dimensional reconstruction pipelines for maize‐root phenotyping
Comparison of open‐source three‐dimensional reconstruction pipelines for maize‐root phenotyping
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DOI：
10.1002/ppj2.20068
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发表时间：
2023-01
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通讯作者：
Suxing Liu;Wesley Paul Bonelli;P. Pietrzyk;Alexander Bucksch
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作者：
Suxing Liu;Wesley Paul Bonelli;P. Pietrzyk;Alexander Bucksch
了解三维（3D）根系特征对于改善水分吸收、增加氮捕获和提高大气中的碳固存至关重要。然而，由于3D根系模型质量和3D根系性状准确性之间的未知权衡，通过重建3D根系模型来量化3D根系性状仍然是一个挑战。因此，我们进行了两个计算实验。我们首先比较了由五个最先进的开源3D模型重建管道在12个对比基因型的田间生长玉米根上生成的3D模型质量。这些管道包括COLMAP，COLMAP+PMVS（基于补丁的多视图立体），VisualSFM，Meshroom和OpenMVG+MVE（多视图环境）。COLMAP流水线在3D模型质量与计算时间和所需图像数量方面实现了最佳性能。在第二个测试中，我们比较了使用基于COLMAP的3D重建的3D根系性状数字成像3D管道（DIRT/3D）与我们目前使用基于VisualSFM的3D重建的DIRT/3D管道在12个基因型的相同数据集上生成的3D根系性状测量的准确性，每个基因型重复5-10次。结果表明：（1）建立一个密集的3D模型所需的平均图像数量从3000减少到3600（DIRT/3D [基于VisualSFM的3D重建]），计算测试1约为360，计算测试2约为600（DIRT/3D [基于COLMAP的3D重建]）;（2）更密集的3D模型有助于提高3D根系性状测量的准确性;（3）减少图像数量有助于解决数据存储问题。更新后的DIRT/3D（基于COLMAP的3D重建）流水线可实现更快的图像采集，而不会影响3D根系性状测量的准确性。
Understanding three‐dimensional (3D) root traits is essential to improve water uptake, increase nitrogen capture, and raise carbon sequestration from the atmosphere. However, quantifying 3D root traits by reconstructing 3D root models for deeper field‐grown roots remains a challenge due to the unknown tradeoff between 3D root‐model quality and 3D root‐trait accuracy. Therefore, we performed two computational experiments. We first compared the 3D model quality generated by five state‐of‐the‐art open‐source 3D model reconstruction pipelines on 12 contrasting genotypes of field‐grown maize roots. These pipelines included COLMAP, COLMAP+PMVS (Patch‐based Multi‐View Stereo), VisualSFM, Meshroom, and OpenMVG+MVE (Multi‐View Environment). The COLMAP pipeline achieved the best performance regarding 3D model quality versus computational time and image number needed. In the second test, we compared the accuracy of 3D root‐trait measurement generated by the Digital Imaging of Root Traits 3D pipeline (DIRT/3D) using COLMAP‐based 3D reconstruction with our current DIRT/3D pipeline that uses a VisualSFM‐based 3D reconstruction on the same dataset of 12 genotypes, with 5–10 replicates per genotype. The results revealed that (1) the average number of images needed to build a denser 3D model was reduced from 3000 to 3600 (DIRT/3D [VisualSFM‐based 3D reconstruction]) to around 360 for computational test 1, and around 600 for computational test 2 (DIRT/3D [COLMAP‐based 3D reconstruction]); (2) denser 3D models helped improve the accuracy of the 3D root‐trait measurement; (3) reducing the number of images can help resolve data storage problems. The updated DIRT/3D (COLMAP‐based 3D reconstruction) pipeline enables quicker image collection without compromising the accuracy of 3D root‐trait measurements.