Image-based 3D digitizing for plant architecture analysis and phenotyping

Functional-structural plant modeling and plant phenotyping require the measurement of geometric features in specimens. This data acquisition is called plant digitizing. Actually, these measurements are performed manually, in invasive or even destructive ways, or using expensive laser scanning equipment. Computer vision based 3D reconstruction is an accurate and low cost alternative for the digitizing of plants not presenting a dense canopy. Sparse canopies are found in several important annual plants in agriculture as soybean and maize, at least in their early stages of development. This paper shows as the state of the art in structure from motion and multiple view stereo is able to produce accurate 3D models for specimens presenting sparse canopies. Threedimensional triangular meshes are computed from a set of noncalibrated images, modeling a basil and an Ixora specimens and accurately representing their leaves and branches. Keywords-plant phenotyping; plant architecture; structure from motion; multiple view stereo;