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Sensors 2016, 16(6), 874;

Estimating 3D Leaf and Stem Shape of Nursery Paprika Plants by a Novel Multi-Camera Photography System

Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan
Author to whom correspondence should be addressed.
Academic Editors: Changzhi Li, Roberto Gómez-García and José-María Muñoz-Ferreras
Received: 12 April 2016 / Revised: 3 June 2016 / Accepted: 6 June 2016 / Published: 14 June 2016
(This article belongs to the Special Issue Non-Contact Sensing)
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For plant breeding and growth monitoring, accurate measurements of plant structure parameters are very crucial. We have, therefore, developed a high efficiency Multi-Camera Photography (MCP) system combining Multi-View Stereovision (MVS) with the Structure from Motion (SfM) algorithm. In this paper, we measured six variables of nursery paprika plants and investigated the accuracy of 3D models reconstructed from photos taken by four lens types at four different positions. The results demonstrated that error between the estimated and measured values was small, and the root-mean-square errors (RMSE) for leaf width/length and stem height/diameter were 1.65 mm (R2 = 0.98) and 0.57 mm (R2 = 0.99), respectively. The accuracies of the 3D model reconstruction of leaf and stem by a 28-mm lens at the first and third camera positions were the highest, and the number of reconstructed fine-scale 3D model shape surfaces of leaf and stem is the most. The results confirmed the practicability of our new method for the reconstruction of fine-scale plant model and accurate estimation of the plant parameters. They also displayed that our system is a good system for capturing high-resolution 3D images of nursery plants with high efficiency. View Full-Text
Keywords: 3D modeling; leaf; stem; accuracy; MCP system; stereovision; MVS; SfM 3D modeling; leaf; stem; accuracy; MCP system; stereovision; MVS; SfM

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Zhang, Y.; Teng, P.; Shimizu, Y.; Hosoi, F.; Omasa, K. Estimating 3D Leaf and Stem Shape of Nursery Paprika Plants by a Novel Multi-Camera Photography System. Sensors 2016, 16, 874.

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