Adaptive Foveated Rendering Radius Adjustment
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Solution Overview
Problem
Current foveated rendering techniques in virtual reality systems often require a larger rendered foveal region than necessary due to variability in human vision and tracking errors, leading to increased computational complexity and unnecessary rendering, which can cause motion sickness and reduce immersion.
Innovation Solution
An adaptive foveated rendering technique that adjusts the fovea rendering radius using error bounds and eye tracking data to compensate for state changes and errors, dynamically resizing the foveal region to balance resolution quality and rendering performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a larger foveal region is rendered at high resolution to account for variability in human vision and tracking errors, then the reliability of visual quality is improved, but the computational complexity increases
Solution Approach 1:
The patent implements dynamic adjustment of the foveal region radius based on real-time eye tracking data and detected eye states. The system transitions from static to dynamic rendering parameters, resizing the foveal region according to actual gaze stability and eye state (open/closed, saccade detection), thereby optimizing the balance between visual quality reliability and computational complexity
Solution Approach 2:
The system changes the rendering parameter (foveal region radius) based on detected eye states and tracking accuracy. By adjusting the radius parameter dynamically according to actual eye behavior, the system adapts the rendered area to match actual visual needs, reducing unnecessary high-resolution rendering while maintaining reliability when needed
2Measurement precision
If the foveal region size is increased to compensate for tracking errors, then the measurement precision of visual coverage is improved, but the rendering performance decreases
Solution Approach 1:
The system uses eye tracking data as feedback to continuously adjust the foveal region size. By monitoring actual gaze position and eye state, the system refines the rendered area to match actual visual coverage needs, improving measurement precision of visual coverage while avoiding excessive rendering by using the feedback to minimize the high-resolution area
Solution Approach 2:
The system applies partial high-resolution rendering only to the necessary foveal region rather than the entire display area. By using eye tracking to identify the precise region requiring high measurement precision, the system avoids excessive rendering actions in peripheral areas where lower resolution suffices, thereby maintaining rendering performance
3Adaptability or versatility
If a fixed large foveal region is rendered, then the adaptability to different eye states is improved, but the loss of time in rendering increases
Solution Approach 1:
The system dynamically adapts the foveal region size based on detected eye states (open/closed, saccade presence) rather than using a fixed large region. This dynamic adaptation allows the system to be versatile across different eye states while minimizing rendering time by only maintaining large foveal regions when actually needed for stable fixation
Solution Approach 2:
The system periodically updates the foveal region size based on continuous eye tracking data and detected eye states. By using periodic detection and adjustment cycles, the system maintains adaptability to changing eye states while avoiding continuous full-resolution rendering, thereby reducing overall rendering time loss
Data Source
AI summary
Foveated rendering based on user gaze tracking may be adjusted to account for the realities of human vision. Gaze tracking error and state parameters may be determined from gaze tracking data representing a user's gaze with respect to one or more images presented to a user. Adjusted foveation data representing an adjusted size and/or shape of one or more regions of interest in one or more images to be subsequently presented to a user may be generated based on the one or more gaze tracking error or state parameters. Foveated image data representing one or more foveated images may be generated with the adjusted foveation data. The foveated images are characterized by level of detail within the one or more regions of interest and lower level of detail outside the one or more regions of interest. The foveated images may then be presented to the user.