![]() ![]() This study aims to evaluate several software packages for dense 3D reconstruction from multiple overlapping RGB images on field and plot-scale. 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. Using multiple CMSs generated from data acquired at multiple time steps, a crop surface monitoring is enabled. Two datasets have been used to compare and evaluate the FOSS applications based on the point clouds they produced. To address the above issues, a set of FOSS were studied based on their offered features, workflow, 3D processing time and accuracy. However, contemporary academic discourse seldom presents survey-based feature lists or a critical inspection of potential production pipelines, nor typically provides direction and guidance for non-experts who are interested in learning, developing and sharing 3D content on a restricted budget. There also exists free and open source FOSS software, with the potential to deliver quality data for heritage documentation purposes. Image-based 3D modelling software, on the other hand, offers a cheaper alternative, which can handle this task with relative ease. The 3D reconstruction of real-world heritage objects using either a laser scanner or 3D modelling software is typically expensive and requires a high level of expertise.
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