Robust image-based 3D Modeling of Root Architecture Luis D. Lopez Deepak Shantharaj Lu Liu Harsh Bais Jingyi Yu

Root system architecture (RSA) plays an important role in plant development and survival. The ability to accurately model and quantify properties of root architecture is fundamental for sustainability stud- ies, crop improvement, and studies of plant-microbal interactions. Existing methods to model RSA either re- quire a dense set of images or rely on 3D scanning meth- ods for dense reconstruction. In this paper, we present an image-based technique for recovering complex 3D root geometry from a sparse set of viewpoints. Our solution incorporates 2D/3D root system topology as shape prior into the geometric reconstruction process. For every input view, we apply image matting for seg- menting the root from the background. We then recover a 2D skeleton graph of the root from its matte im- age and nd its corresponding 2D topology tree from the skeleton graph. Next, we present an iterative al- gorithm for computing the 3D topology tree that is most consistent with the set of 2D topology trees. Fi- nally, we apply volumetric reconstruction for recover- ing the complete 3D root model from its 3D topology tree. We demonstrate our framework on roots of rice