Abstract
Accurate high-resolution 3D models are essential for a non-invasive analysis of phenotypic characteristics of plants. Leaf surface areas, fruit volumes and leaf inclination angles are typically of interest. This work presents a globally optimal 3D geometry reconstruction method that is specialized to high-resolutions and is thus suitable to reconstruct thin structures typically occuring in the geometry of plants. Volumetric 3D models are computed in a convex optimization framework from a set of RGB input images depicting the plant from different view points. The method uses the memory and run-time efficient octree data structure for fast computations of high-resolution 3D models. Results show accurate 3D reconstructions of barley, while an increase in resolution of a factor of up to 2000 is achieved in comparison to the use of a uniform voxel based data structure, making the choice of data structure crucial for feasible resolutions.
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Klodt, M., Cremers, D. (2015). High-Resolution Plant Shape Measurements from Multi-view Stereo Reconstruction. In: Agapito, L., Bronstein, M., Rother, C. (eds) Computer Vision - ECCV 2014 Workshops. ECCV 2014. Lecture Notes in Computer Science(), vol 8928. Springer, Cham. https://doi.org/10.1007/978-3-319-16220-1_13
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DOI: https://doi.org/10.1007/978-3-319-16220-1_13
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