EVALUATING DENSE 3D RECONSTRUCTION SOFTWARE PACKAGES FOR OBLIQUE MONITORING OF CROP CANOPY SURFACE

Abstract

Crop Surface Models (CSMs) are 2.5D raster surfaces representing absolute plant canopy height. Using multiple CMSs generated from data acquired at multiple time steps, a crop surface monitoring is enabled. This makes it possible to monitor crop growth over time and can be used for monitoring in-field crop growth variability which is useful in the context of high-throughput phenotyping. This study aims to evaluate several software packages for dense 3D reconstruction from multiple overlapping RGB images on field and plot-scale. A summer barley field experiment located at the Campus Klein-Altendorf of University of Bonn was observed by acquiring stereo images from an oblique angle using consumer-grade smart cameras. Two such cameras were mounted at an elevation of 10 m and acquired images for a period of two months during the growing period of 2014. The field experiment consisted of nine barley cultivars that were cultivated in multiple repetitions and nitrogen treatments. Manual plant height measurements were carried out at four dates during the observation period. The software packages Agisoft PhotoScan, VisualSfM with CMVS/PMVS2 and SURE are investigated. The point clouds are georeferenced through a set of ground control points. Where adequate results are reached, a statistical analysis is performed.

Plant phenotyping relevance

複数のソフトウェアによるRGB画像からの密な3D再構成を評価し、作物キャノピー高を推定・検証する研究であり、植物表現型取得手法が中心です。

Code and data availability

The paper evaluates PhotoScan, SURE, and VisualSfM/CMVS-PMVS2 for crop surface modeling from oblique stereo imagery of a barley field. No public phenotype dataset, image collection, author analysis code, or supplement is deposited; the only URLs mentioned are the CROP.SENSe network homepage, a GRASS GIS add-on manual,

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