3D Rendering Controller With On-Surface Cache Sharing for Multi-Viewer Shading
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Solution Overview
Problem
Conventional methods for computing shading in complex lighting scenarios of 3D virtual environments with multiple moving light sources are inefficient and costly, particularly in multi-viewer applications, due to the need for individual rendering computations and reliance on costly statistical techniques like importance sampling.
Innovation Solution
A rendering controller utilizing on-surface weighted reservoir resampling (OSWRR) for sharing lighting computations across time and space, employing resampled importance sampling (RIS) and weighted reservoir sampling (WRS) based on on-surface caches to efficiently compute direct and indirect illumination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional importance sampling is used to compute shading in complex lighting scenarios, then illumination estimation accuracy is improved, but computation cost and processing time increase significantly
Solution Approach 1:
The system performs preliminary light transport computations and stores results in on-surface caches before they are needed for rendering. By pre-computing illumination data and caching it on surfaces, the system avoids performing expensive importance sampling computations in real-time, thus reducing processing time while maintaining accuracy.
Solution Approach 2:
The system creates copies of computed light transport data and stores them in on-surface caches. Instead of重新 computing illumination for each viewer or time step, the system copies previously computed results from the cache, significantly reducing computation time while preserving illumination estimation accuracy.
2Measurement precision
If individual rendering computations are performed for each viewer in multi-viewer applications, then view-specific rendering accuracy is improved, but processing power consumption increases
Solution Approach 1:
The system merges rendering computations across multiple viewers by identifying common light transport paths and computing them once. The on-surface caches store merged results that can be shared among multiple viewers, reducing redundant computations and processing power consumption while maintaining view-specific rendering accuracy through selective application of cached data.
Solution Approach 2:
The on-surface caches serve multiple functions and multiple viewers simultaneously. A single cached light transport computation can be universally applied to illuminate multiple surfaces visible to different viewers, making the rendering system more efficient without sacrificing view-specific accuracy.
3Productivity
If on-surface weighted reservoir resampling is used to share lighting computations, then processing efficiency is improved, but system complexity increases
Solution Approach 1:
The on-surface caches act as intermediaries between light sources and surfaces, mediating the light transport computations. These caches store pre-computed illumination data and provide it to multiple viewers, improving processing efficiency while managing system complexity through a structured caching mechanism that organizes data efficiently.
Data Source
AI summary
A rendering controller configured to render lights in a three-dimensional (3D) scene is disclosed. The 3D scene includes one or more objects. Each object is associated with a plurality of on-surface reservoirs. The rendering controller is further configured to provide light transport computation in texture space utilizing resampled importance sampling (RIS) or weighted reservoir sampling (WRS) based on the on-surface caches. The rendering controller is configured to compute shading efficiently (i.e., direct, and indirect illumination) of the 3D scene in multi-viewer applications present in the cloud, which involves complex lighting scenarios.