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High-Resolution Plant Shape Measurements from Multi-view Stereo Reconstruction

  • Maria KlodtEmail author
  • Daniel Cremers
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8928)

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.

Keywords

Stereo Reconstruction Convex Optimization Plant Phenotyping Octrees 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Technische Universität MünchenMunichGermany

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