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Tree model simplification with hybrid polygon/billboard approach and human-centered quality evaluation

We propose a tree model simplification method based on a hybrid polygon/billboard approach in this work. The objective is to create a simplified tree model with lower polygon counts while preserving the visual appearance of the original model. The result is suitable for human viewing from different angles around the tree as well as close up views. In the simplification process, a subset of polygons is carefully chosen to speed up the rendering process, and textures with a different number of leaves are mapped to scaled polygons based on the density of polygon's position on the tree. For objective performance evaluation, saliency maps of rendered images of simplified and original models are generated and the mean-squared-error (MSE) between them is calculated to quantify their resemblance. Furthermore, it is shown that feature maps (e.g., the intensity, orientation, and color maps of an image) can be utilized to simplify the tree model more aggressively since they provide means to highlight human visual attention. Finally, a subjective test is conducted to rate different simplification algorithms. Experimental results indicate that the proposed hybrid polygon/billboard method has better performance than other benchmarking methods in both objective and subjective evaluations.