Importance Point Projection for GPU-based Final Gathering
| dc.contributor.author | Maletz, David | en_US |
| dc.contributor.author | Wang, Rui | en_US |
| dc.contributor.editor | Ravi Ramamoorthi and Erik Reinhard | en_US |
| dc.date.accessioned | 2015-02-27T14:45:42Z | |
| dc.date.available | 2015-02-27T14:45:42Z | |
| dc.date.issued | 2011 | en_US |
| dc.description.abstract | We present a practical importance-driven method for GPU-based final gathering. We take as input a point cloud representing directly illuminated scene geometry; we then project and splat the points to microbuffers, which store each shading pixel's occluded radiance field. We select points for projection based on importance, defined as each point's estimated contribution to a shading pixel. For each selected point, we calculate its splat size adaptively based on its importance value. The main advantage of our method is that it's simple and fast, and provides the capability to incorporate additional importance factors such as glossy reflection paths. We also introduce an image-space adaptive sampling method, which combines adaptive image subdivision with joint bilateral upsampling to robustly preserve fine details. We have implemented our algorithm on the GPU, providing high-quality rendering for dynamic scenes at near interactive rates. | en_US |
| dc.description.seriesinformation | Computer Graphics Forum | en_US |
| dc.identifier.issn | 1467-8659 | en_US |
| dc.identifier.uri | https://doi.org/10.1111/j.1467-8659.2011.01992.x | en_US |
| dc.publisher | The Eurographics Association and Blackwell Publishing Ltd. | en_US |
| dc.title | Importance Point Projection for GPU-based Final Gathering | en_US |