Hypothesis Testing for Progressive Kernel Estimation and VCM Framework

Lin, Zuoquan; Hu, Chenxiao; Jia, Jinzhu; Li, Sheng

doi:10.1109/tvcg.2023.3274595

IEEE Trans. Visual. Comput. Graphics

2024

DOI: 10.1109/tvcg.2023.3274595

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Hypothesis Testing for Progressive Kernel Estimation and VCM Framework

Zuoquan Lin

Chenxiao Hu

Jinzhu Jia

et al.

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Proxy Tracing: Unbiased Reciprocal Estimation for Optimized Sampling in BDPT

Su,

Li,

Yin

et al. 2024

ACM Trans. Graph.

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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.

show abstract

Proxy Tracing: Unbiased Reciprocal Estimation for Optimized Sampling in BDPT

Su,

Li,

Yin

et al. 2024

ACM Trans. Graph.

View full text Add to dashboard Cite

show abstract

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Hypothesis Testing for Progressive Kernel Estimation and VCM Framework

Cited by 1 publication

References 31 publications

Proxy Tracing: Unbiased Reciprocal Estimation for Optimized Sampling in BDPT

Proxy Tracing: Unbiased Reciprocal Estimation for Optimized Sampling in BDPT

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