Tree model reconstruction innovization using multi-objective differential evolution

This paper presents an innovization design principle for procedural tree model of woody plants (trees) reconstruction by multi-objective optimization. Reconstruction of a parameterized procedural model from imagery is addressed by a multi-objective differential evolution algorithm, which evolves a parametrized procedural model by fitting a set of its rendered images to a set of given projected images using bi-objective comparisons made on a pixel level of the images. The use of multi-objective approach gives the decision maker a chance to select the final resulting model, and helps determine the optimization criteria tradeoff weights for later production.