Photon-Driven Manifold Sampling

Complex lighting phenomenon such as the caustics often arises from specular chains of varying lengths. Thanks to recent advancement in specular light transport, we are able to address most effects caused by shorter specular chains using root-finding techniques. However, finding longer chains of valid specular interaction still remains problematic due to the curse of dimensionality. This creates a difficulty for methods that depend on random sampling to navigate the path space. In this paper, we present Photon-Driven Manifold Sampling (PMS), an unbiased method designed for sampling multi-bounce caustics, derived from Specular Manifold Sampling (SMS). We achieve efficient caustic rending through the combination of photon mapping and path space manifold exploration. Our method, inspired by recent advancements in path reusing techniques, caches multi-bounce caustic photons with the aim of reusing their vertices to seed local exploration via manifold walk. This eliminates the necessity for additional random sampling in seed path sampling as seen in alternative methods that took the guiding approach. Our results highlight a notable decrease in variance compared to other state-of-the-art techniques and demonstrate the adaptability to intricate specular chains.

Authors

Institutions

Publication Details

Journal
Proceedings of the ACM on Computer Graphics and Interactive Techniques
Published
2024-08-09
DOI
https://doi.org/10.1145/3675375
Primary Topic
Image Enhancement Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Photon-Driven Manifold Sampling

Chun‐Fa Chang, Fei Lee, Jia‐Wun Jhang
Proceedings of the ACM on Computer Graphics and Interactive Techniques
Image Enhancement Techniques
article

Photon-Driven Manifold Sampling

Chun‐Fa Chang, Fei Lee, Jia‐Wun Jhang
article en

Abstract

Complex lighting phenomenon such as the caustics often arises from specular chains of varying lengths. Thanks to recent advancement in specular light transport, we are able to address most effects caused by shorter specular chains using root-finding techniques. However, finding longer chains of valid specular interaction still remains problematic due to the curse of dimensionality. This creates a difficulty for methods that depend on random sampling to navigate the path space. In this paper, we present Photon-Driven Manifold Sampling (PMS), an unbiased method designed for sampling multi-bounce caustics, derived from Specular Manifold Sampling (SMS). We achieve efficient caustic rending through the combination of photon mapping and path space manifold exploration. Our method, inspired by recent advancements in path reusing techniques, caches multi-bounce caustic photons with the aim of reusing their vertices to seed local exploration via manifold walk. This eliminates the necessity for additional random sampling in seed path sampling as seen in alternative methods that took the guiding approach. Our results highlight a notable decrease in variance compared to other state-of-the-art techniques and demonstrate the adaptability to intricate specular chains.

Proceedings of the ACM on Computer Graphics and Interactive TechniquesVol. 7(3)
National Taiwan Normal University (TW)
Openalex Percentile: Top 88%
Image Enhancement Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Photon-Driven Manifold Sampling — Chun‐Fa Chang, Fei Lee, et al. · Proceedings of the ACM on Computer Graphics and Interactive Techniques (2024) | TGRS Research Map | TGRS