Robust image-based 3D Modeling of Root Architecture

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 studies, crop improvement, and studies of plant-microbal interactions. Existing methods to model RSA either require a dense set of images or rely on 3D scanning methods 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 segmenting the root from the background. We then recover a 2D skeleton graph of the root from its matte image and find its corresponding 2D topology tree from the skeleton graph. Next, we present an iterative algorithm for computing the 3D topology tree that is most consistent with the set of 2D topology trees. Finally, we apply volumetric reconstruction for recovering the complete 3D root model from its 3D topology tree. We demonstrate our framework on roots of rice L. D. Lopez University of Delaware E-mail: [email protected] D. Shantharaj University of Delaware E-mail: [email protected] L. Liu Washington University in St. Louis E-mail: [email protected] H. Bais University of Delaware E-mail: [email protected] J. Yu University of Delaware E-mail: [email protected] (Oryza sativa) and brachypodium (B. distachyon) and our experiments show that our method is robust and accurate.