Adaptive Virtual Camera Sampling to Reduce Ray-Tracing Latency

Solution Overview

Problem

Existing ray tracing techniques consume excessive processing resources and introduce latency due to indiscriminate sampling of pixels, which is undesirable in many applications.

Innovation Solution

Adaptive sampling techniques are employed to intelligently select the number of light ray samples based on foreknowledge of the scene, allowing for non-uniform sampling of different scene portions, reducing the total number of samples required and incorporating post-rendering denoising to enhance image quality.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If indiscriminate sampling of pixels is used in path-tracing, then image quality can be maintained, but processing resources are consumed excessively and latency increases

Engineering Contradiction:

Improveimage qualityVSAvoidprocessing resources and latency

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent applies local quality by differentiating sampling strategies across different image regions. High-frequency regions (edges, textures) receive higher sampling rates while low-frequency regions (smooth areas) receive lower sampling rates. This is implemented through adaptive sampling that analyzes scene content and adjusts per-pixel or per-region sampling counts, thereby maintaining image quality where needed while reducing overall processing resources.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent implements dynamics through adaptive sampling that adjusts sampling rates dynamically based on scene analysis. The system evaluates scene properties (such as texture complexity, edge density, and spatial frequency) and modifies sampling strategies in real-time. This dynamic adjustment allows the system to optimize between image quality and processing efficiency for each specific rendering scenario.

Inventive Principle:

Principle #15Dynamics

2Stability of the object's composition

If uniform sampling of all pixels is performed, then rendering consistency is maintained, but processing time increases due to unnecessary samples in low-complexity regions

Engineering Contradiction:

Improverendering consistencyVSAvoidprocessing time

Core Design Contradiction:

Stability of the object's compositionVSLoss of time

Solution Approach 1:

The patent applies local quality by differentiating sampling strategies across different image regions. High-frequency regions (edges, textures) receive higher sampling rates while low-frequency regions (smooth areas) receive lower sampling rates. This is implemented through adaptive sampling that analyzes scene content and adjusts per-pixel or per-region sampling counts, thereby maintaining image quality where needed while reducing overall processing resources.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent implements parameter changes by varying the sampling rate parameter across different image regions based on scene complexity analysis. The system changes sampling parameters (number of samples, sample distribution) according to detected scene properties such as texture complexity and spatial frequency variations, optimizing the balance between rendering consistency and processing time.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS12374022B2Adaptive virtual camera sensor

Publication Date: 2025.07.29 OUTWARD INC

AI summary

Techniques associated with adaptive sampling are disclosed. In some embodiments, in response to receiving a specification of a scene to render, a sampling of each portion of the scene is determined based at least in part on the specification of the scene such that the scene is not uniformly sampled, and the scene is rendered according to the determined sampling of each portion of the scene.