Interactive Modeling of Tree Bark from a Single Image

There exist many computer graphics techniques which could achieve high quality tree generation. However, only a few works focus on realistic modeling of tree bark. Difficulties lie in the complex appearance of the bark surfaces which are largely determined by their mesostructures. Unlike traditional physical based methods, in this paper, we present an appearance-based method to model tree bark surfaces from a single image. We address three main issues here: feature specification, height field assignment and texture correction. For feature specification, we use texton channel analysis to specify a variant of common bark features, including ironbark, vertical and horizontal fractures, tessellation, furrowed cork, and lenticels. For height field assignment, we develop an intuitive and easy-to-use user interface (UI). Here similarity-based texture editing is used for assigning height fields within a texton channel mask. For texture correction, we use the modeled height fields to eliminate the underlying lighting effects in a captured texture. Our modeling system is image-based: it takes as input a bark image and produces as output a textured height field representing a bark sample. We demonstrate that our method is an effective and easy-to-use technique to interactively model a variety of photo realistic bark surfaces.