We present a lobe-based tree representation for modeling trees. The new representation is based on the observation that the tree's foliage details can be abstracted into canonical geometry structures, termed lobe-textures. We introduce techniques to (i) approximate the geometry of given tree data and encode it into a lobe-based representation, (ii) decode the representation and synthesize a fully detailed tree model that visually resembles the input. The encoded tree serves as a light intermediate representation, which facilitates efficient storage and transmission of massive amounts of trees, e.g., from a server to clients for interactive applications in urban environments. The method is evaluated by both reconstructing laser scanned trees (given as point sets) as well as re-representing existing tree models (given as polygons).

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.