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| Content Provider | ACM Digital Library |
|---|---|
| Author | Chenney, Stephen Fan, Shaohua Lai, Yu-chi |
| Abstract | We present Metropolis Photon Sampling (MPS), a visual importance-driven algorithm for populating photon maps. Photon Mapping and other particle tracing algorithms fail if the photons are poorly distributed. Our approach samples light transport paths that join a light to the eye, which accounts for the viewer in the sampling process and provides information to improve photon storage. Paths are sampled with a Metropolis-Hastings algorithm that exploits coherence among important light paths. We also present a technique for including user selected paths in the sampling process without introducing bias. This allows a user to provide hints about important paths or reduce variance in specific parts of the image. We demonstrate MPS with a range of scenes and show quantitative improvements in error over standard Photon Mapping and Metropolis Light Transport. |
| Starting Page | 127 |
| Ending Page | 138 |
| Page Count | 12 |
| ISBN | 3905673231 |
| ISSN | 17273463 |
| DOI | 10.2312/EGWR/EGSR05/127-138 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2005-06-29 |
| Publisher Place | Goslar |
| Access Restriction | Subscribed |
| Content Type | Text |
| Resource Type | Article |
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