Automatic reconstruction of tree skeletal structures from point clouds

Abstract

Trees, bushes, and other plants are ubiquitous in urban environments, and realistic models of trees can add a great deal of realism to a digital urban scene. There has been much research on modeling tree structures, but limited work on reconstructing the geometry of real-world trees -- even then, most works have focused on reconstruction from photographs aided by significant user interaction. In this paper, we perform active laser scanning of real-world vegetation and present an automatic approach that robustly reconstructs skeletal structures of trees, from which full geometry can be generated. The core of our method is a series of global optimizations that fit skeletal structures to the often sparse, incomplete, and noisy point data. A significant benefit of our approach is its ability to reconstruct multiple overlapping trees simultaneously without segmentation. We demonstrate the effectiveness and robustness of our approach on many raw scans of different tree varieties.