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Section: New Results
Complex Scenes
In order to render both efficiently and accurately ultra-detailed large scenes, this approach consists in developing representations and algorithms able to account compactly for the quantitative visual appearance of a regions of space projecting on screen at the size of a pixel.
Appearance pre-filtering
Participants : Guillaume Loubet, Fabrice Neyret.
We address the problem of constructing appearance-preserving level of details (LoDs) of complex 3D models such as trees and propose a hybrid method that combines the strength of mesh and volume representations. Our main idea is to separate macroscopic (i.e. larger than the target spatial resolution) and microscopic (sub-resolution) surfaces at each scale and to treat them differently, because meshes are very efficient at representing macroscopic surfaces while sub-resolution geometry benefit from volumetric approximations. We introduce a new algorithm based on mesh analysis that detects the macroscopic surfaces of a 3D model at a given resolution. We simplify these surfaces with edge collapses and provide a method for pre-filtering their BRDFs parameters. To approximate microscopic details, we use a heterogeneous microflake participating medium and provide a new artifact-free voxelization algorithm that preserves local occlusion. Thanks to our macroscopic surface analysis, our algorithm is fully automatic and can generate seamless LoDs at arbitrarily coarse resolutions for a wide range of 3D models. We validated our method on highly complex geometry and show that appearance is consistent across scales while memory usage and loading times are drasticall y reduced (see Figure 12). This work has been submitted to EG2017.
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