Enhanced 3d tree model simplification and perceptual analysis

The effectiveness of 3D tree model simplification techniques and their objective and subjective performance evaluations are examined in this work. The simplification techniques developed in were based on pixel-based metrics, which did not consider the tree model´s leaf density. For performance improvement, we perform simplification based on the tree leaf density of rendered images viewed from multiple angles. Furthermore, objective performance analysis is conducted to evaluate how well different algorithms are able to simplify tree models that appear as close to the original tree model with a given budget on the number of tree leaves in the model. To this end, a performance metric based on the Gabor filter is developed to analyze the orientation and spatial relationship within the rendered tree models. Finally, subjective evaluation is conducted by a group of 23 people. Both the objective and the subject evaluations reach a consistent conclusion; namely, the newly proposed density-based simplification technique offers the best results.