3D reconstruction using Structure-from-Motion: a new technique for morphological measurement of tree root systems
3D reconstruction using Structure-from-Motion: a new technique for morphological measurement of tree root systems
复制标题
使用运动结构进行 3D 重建:树根系统形态测量的新技术
DOI:
10.1007/s11104-022-05448-8
复制
发表时间:
2022
期刊:
影响因子:
4.9
通讯作者:
Ohashi Mizue
中科院分区:
文献类型:
--
作者:
Okamoto Yuki;Ikeno Hidetoshi;Hirano Yasuhiro;Tanikawa Toko;Yamase Keitaro;Todo Chikage;Dannoura Masako;Ohashi Mizue
PurposeClarification of root architecture is important for understanding tree root functions. 3D laser scanning reconstructs the 3D structure of root system with high accuracy, but the devices are large and expensive. The Structure-from-Motion with multi-view stereo-photogrammetry (SfM-MVS) method reconstructs the 3D structure of an object from multiple images. This method is suitable for field research because it acquires the 3D data with a commercially available digital camera. Our aim in this study was to test the applicability of the SfM-MVS method for morphological measurement of tree root systems.MethodsThe 3D root system model was created using a dummy and three black pine (Pinus thunbergii) root systems. Image data were collected from the root systems using a camera and reconstructed using the free software, VisualSfM and MeshLab. We evaluated the accuracy of morphological data estimated from the 3D models by comparing them with real data obtained from manual measurements of the root systems.ResultsThe 3D reconstructions of the dummy and black pine root systems were successful. The root mean squared error values for the morphological features in the pine root systems ranged from 4 to 24%, which was sufficiently accurate for a successful 3D model. However, the RMSE values were larger than that of dummy root, ranging from 2 to 9%.ConclusionThe SfM-MVS method is a new tool, based on non-specialised equipment and free software, to obtain the 3D structure of tree root systems. The morphological features of it can be successfully measured from the reconstructed models.
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DOI:
10.5194/isprs-archives-xlii-2-w3-551-2017
发表时间:
2017
期刊:
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
影响因子:
--
作者:
E. Oniga;C. Chirila;F. Stătescu
通讯作者:
F. Stătescu
影响因子:
2.7
作者:
House JE;Brambilla V;Bidaut LM;Christie AP;Pizarro O;Madin JS;Dornelas M
通讯作者:
Dornelas M
DOI:
--
发表时间:
2009
期刊:
影响因子:
--
作者:
H. Gärtner;B. Wagner;I. Heinrich;C. Denier
通讯作者:
C. Denier
影响因子:
3.8
作者:
K. Yamase;C. Todo;N. Torii;T. Tanikawa;Tomonori Yamamoto;H. Ikeno;M. Ohashi;M. Dannoura;Y. Hirano
通讯作者:
K. Yamase;C. Todo;N. Torii;T. Tanikawa;Tomonori Yamamoto;H. Ikeno;M. Ohashi;M. Dannoura;Y. Hirano
影响因子:
6.4
作者:
Andrew K. Koeser;John W. Roberts;Jason W. Miesbauer;Angélica Bannwart Lopes;G. Kling;Marvin Lo;J. Morgenroth
通讯作者:
J. Morgenroth