EMCA: Explorer of Monte Carlo based Algorithms
| dc.contributor.author | Ruppert, Lukas | en_US |
| dc.contributor.author | Kreisl, Christoph | en_US |
| dc.contributor.author | Blank, Nils | en_US |
| dc.contributor.author | Herholz, Sebastian | en_US |
| dc.contributor.author | Lensch, Hendrik P. A. | en_US |
| dc.contributor.editor | Andres, Bjoern and Campen, Marcel and Sedlmair, Michael | en_US |
| dc.date.accessioned | 2021-09-25T16:36:29Z | |
| dc.date.available | 2021-09-25T16:36:29Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | Debugging or analyzing the performance of global illumination algorithms is a challenging task due to the complex path-scene interaction and numerous places where errors and programming bugs can occur. We present a novel, lightweight visualization tool to aid in the understanding of global illumination and the debugging of rendering frameworks. The tool provides detailed information about intersections and light transport paths. Users can add arbitrary data of their choosing to each intersection, based on their specific demands. Aggregate plots allow users to quickly discover and select outliers for further inspection across the globally linked visualization views. That information is further coupled with 3D visualization of the scene where additional aggregated information on the surfaces can be inspected in false colors. These include 3D heat maps such as the density of intersections as well as more advanced colorings such as a diffuse transport approximation computed from local irradiance samples and diffuse material approximations. The necessary data for the 3D coloring is collected as a side-product of quickly rendering the image at low sample counts without significantly slowing down the rendering process. It requires almost no precomputation and very little storage compared to point cloud-based approaches. We present several use cases of how novices and advanced rendering researchers can leverage the presented tool to speed up their research. | en_US |
| dc.description.sectionheaders | Visual Parameter Space Analysis | |
| dc.description.seriesinformation | Vision, Modeling, and Visualization | |
| dc.identifier.doi | 10.2312/vmv.20211377 | |
| dc.identifier.isbn | 978-3-03868-161-8 | |
| dc.identifier.pages | 109-116 | |
| dc.identifier.uri | https://doi.org/10.2312/vmv.20211377 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/vmv20211377 | |
| dc.publisher | The Eurographics Association | en_US |
| dc.subject | Computing methodologies | |
| dc.subject | Ray tracing | |
| dc.subject | Human centered computing | |
| dc.subject | Visualization toolkits | |
| dc.subject | Heat maps | |
| dc.title | EMCA: Explorer of Monte Carlo based Algorithms | en_US |
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