Abstract

Robust light transport algorithms, particularly bidirectional path tracing (BDPT), face significant challenges when dealing with specular or highly glossy involved paths. BDPT constructs the full path by connecting sub-paths traced individually from the light source and camera. However, it remains difficult to sample by connecting vertices on specular and glossy surfaces with narrow-lobed BSDF, as it poses severe constraints on sampling in the feasible direction. To address this issue, we propose a novel approach, called proxy sampling, that enables efficient sub-path connection of these challenging paths. When a low-contribution specular/glossy connection occurs, we drop out the problematic neighboring vertex next to this specular/glossy vertex from the original path, then retrace an alternative sub-path as a proxy to complement this incomplete path. This newly constructed complete path ensures that the connection adheres to the constraint of the narrow lobe within the BSDF of the specular/glossy surface. Unbiased reciprocal estimation is the key to our method to obtain a probability density function (PDF) reciprocal to ensure unbiased rendering. We derive the reciprocal estimation method and provide an efficiency-optimized setting for efficient sampling and connection. Our method provides a robust tool for substituting problematic paths with favorable alternatives while ensuring unbiasedness. We validate this approach in the probabilistic connections BDPT for addressing specular-involved difficult paths. Experimental results have proved the effectiveness and efficiency of our approach, showcasing high-performance rendering capabilities across diverse settings.

BibTex

              @article{10.1145/3658216,
                author = {Su, Fujia and Li, Bingxuan and Yin, Qingyang and Zhang, Yanchen and Li, Sheng},
                title = {Proxy Tracing: Unbiased Reciprocal Estimation for Optimized Sampling in BDPT},
                year = {2024},
                issue_date = {July 2024},
                publisher = {Association for Computing Machinery},
                address = {New York, NY, USA},
                volume = {43},
                number = {4},
                issn = {0730-0301},
                url = {https://doi.org/10.1145/3658216},
                doi = {10.1145/3658216},
                journal = {ACM Trans. Graph.},
                month = {jul},
                articleno = {97},
                numpages = {21},
                keywords = {bidirectional path tracing, reciprocal estimation, importance sampling, proxy sampling, difficult path}
                }