Abstract
Volume carving is a well established method for visual hull reconstruction and has been successfully applied in plant phenotyping, especially for 3d reconstruction of small plants and seeds. When imaging larger plants at still relatively high spatial resolution (≤1 mm), well known implementations become slow or have prohibitively large memory needs. Here we present and evaluate a computationally efficient algorithm for volume carving, allowing e.g., 3D reconstruction of plant shoots. It combines a well-known multi-grid representation called “Octree” with an efficient image region integration scheme called “Integral image.” Speedup with respect to less efficient octree implementations is about 2 orders of magnitude, due to the introduced refinement strategy “Mark and refine.” Speedup is about a factor 1.6 compared to a highly optimized GPU implementation using equidistant voxel grids, even without using any parallelization. We demonstrate the application of this method for trait derivation of banana and maize plants.
Highlights
Complementary to genomics, the quantitative description of plant phenotypes is at the core of basic research for the analysis of plant development and physiological responses to abiotic and biotic challenges as well as for applications in plant genetic improvement and precision agriculture
We implemented and tested a fast and reliable volume carving algorithm based on octrees
Octree as multigrid approach and integral image for reliable and fast foreground testing have been used successfully with volume carving in medical applications (Ladikos et al, 2008) and human pose reconstruction (Kanaujia et al, 2013)
Summary
Complementary to genomics, the quantitative description of plant phenotypes is at the core of basic research for the analysis of plant development and physiological responses to abiotic and biotic challenges as well as for applications in plant genetic improvement and precision agriculture. Studies were conducted in Arabidopsis using light-field cameras for depth reconstruction of rosettes (Apelt et al, 2015), in tobacco using high-resolution 3D imaging and a mesh approach (Paproki et al, 2012), and in the field using stereo imaging with consumer cameras (Müller-Linow et al, 2015) Progress in this field is still limited by the required computational power and time investment for image analysis (Minervini et al, 2015). Improvements are required both for methods using 3D reconstruction from silhouettes and 3D imaging
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
