Foveated Rendering Latency Reduction via Scene Analysis
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Solution Overview
Problem
In electronic devices, foveated rendering of graphics content can be inaccurate due to tracking errors and latency when relying on user gaze tracking, leading to suboptimal rendering of high-resolution areas of interest.
Innovation Solution
An apparatus and method that utilize a fovea estimation engine to predict areas of interest based on scene information, allowing a rendering engine to perform predictive adjustments to reduce latency by comparing evaluation metrics across different parts of the graphics content, thereby foveating the area of interest without relying on real-time eye tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time eye tracking is used to identify areas of interest for foveated rendering, then the rendering can be tailored to user gaze, but tracking errors and latency cause inaccurate foveation
Solution Approach 1:
The system performs preliminary analysis of scene information (object importance, motion, complexity) to predict areas of interest before rendering. This advance preparation eliminates the need for real-time eye tracking during rendering, reducing latency while maintaining accurate foveation by pre-identifying which regions require high-resolution processing.
Solution Approach 2:
The system introduces an intermediary evaluation metric that assesses scene characteristics (object importance, motion, complexity) as a mediator between raw scene data and foveation decisions. This intermediary layer provides more reliable area-of-interest identification than direct eye tracking alone, reducing both latency and tracking errors.
2Manufacturing precision
If high-resolution rendering is applied to all areas of graphics content, then rendering quality is maximized, but processing time and computational resources increase significantly
Solution Approach 1:
The system applies different rendering qualities to different regions of the graphics content based on evaluated importance metrics. High-resolution rendering is concentrated only on predicted areas of interest (such as important objects or regions with complex details), while peripheral or less important regions use lower resolution. This local differentiation maintains overall rendering quality while significantly improving processing speed and reducing computational load.
3Measurement precision
If foveated rendering is based on traditional gaze tracking, then only a single area can be foveated at a time, but multiple important areas may be missed
Solution Approach 1:
The system segments the graphics content into multiple independent evaluation units (such as objects or regions) and evaluates each separately using the scene information metrics. This segmentation allows the system to identify and foveate multiple distinct areas of interest simultaneously, rather than being limited to a single gaze point. Each segment can be independently processed and rendered at appropriate resolution levels.
Data Source
AI summary
An apparatus is configured to render graphics content to reduce latency of the graphics content. The apparatus includes a display configured to present graphics content including a first portion corresponding to an area of interest and further including a second portion. The apparatus further includes a fovea estimation engine configured to generate an indication of the area of interest based on scene information related to the graphics content. The apparatus further includes a rendering engine responsive to the fovea estimation engine. The rendering engine is configured to perform a comparison of a first result of an evaluation metric on part of the area of interest with a second result of the evaluation metric with another part of the area of interest. The rendering engine is further configured to render the graphics content using predictive adjustment to reduce latency based on the comparison.