Procedural tree models have been popular in computer graphics for their ability to generate a variety of output trees from a set of input parameters and to simulate plant interaction with the environment for a realistic placement of trees in virtual scenes. However, defining such models and their parameters is a difficult task. We propose an inverse modeling approach for stochastic trees that takes polygonal tree models as input and estimates the parameters of a procedural model so that it produces trees similar to the input. Our framework is based on a novel parametric model for tree generation and uses Monte Carlo Markov Chains to find the optimal set of parameters. We demonstrate our approach on a variety of input models obtained from different sources, such as interactive modeling systems, reconstructed scans of real trees, and developmental models.
@article{Stava2014InverseProceduralModelling, author = {O. Stava, S. Pirk, J. Kratt, B. Chen, R. Měch, O. Deussen, B. Benes}, doi = {10.1111/cgf.12282}, issn = {1467-8659}, journal = {Computer Graphics Forum}, keywords = {mesh generation, biological modeling, natural phenomena, I.3.5 [Computer Graphics]: Computational Geometry and Object Modelling; I.3.6 [Computer Graphics]: Methodology and Techniques Interaction Techniques I.6.8 [Simulation and Modelling]: Types of Simulation Visual}, number = {6}, pages = {118--131}, title = {Inverse Procedural Modelling of Trees}, url = {http://graphics.uni-konstanz.de/publikationen/Stava2014InverseProceduralModelling}, volume = {33}, year = {2014} }