  Thin leaves, fine stems, self-occlusion, non-rigid and slowly changing
structures make plants difficult for three-dimensional (3D) scanning and
reconstruction -- two critical steps in automated visual phenotyping. Many
current solutions such as laser scanning, structured light, and multiview
stereo can struggle to acquire usable 3D models because of limitations in
scanning resolution and calibration accuracy. In response, we have developed a
fast, low-cost, 3D scanning platform to image plants on a rotating stage with
two tilting DSLR cameras centred on the plant. This uses new methods of camera
calibration and background removal to achieve high-accuracy 3D reconstruction.
We assessed the system's accuracy using a 3D visual hull reconstruction
algorithm applied on 2 plastic models of dicotyledonous plants, 2 sorghum
plants and 2 wheat plants across different sets of tilt angles. Scan times
ranged from 3 minutes (to capture 72 images using 2 tilt angles), to 30 minutes
(to capture 360 images using 10 tilt angles). The leaf lengths, widths, areas
and perimeters of the plastic models were measured manually and compared to
measurements from the scanning system: results were within 3-4% of each other.
The 3D reconstructions obtained with the scanning system show excellent
geometric agreement with all six plant specimens, even plants with thin leaves
and fine stems.
