Gaze-Adaptive Image Rendering for HMDs
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Solution Overview
Problem
Existing gaze tracking systems in head-mountable display units (HMDs) face challenges in accurately and efficiently determining user gaze direction for optimized image rendering, particularly in resource-constrained environments, as they often require significant processing power without noticeable degradation in image quality.
Innovation Solution
The implementation of a modified image rendering system that utilizes gaze tracking data to dynamically adjust pixel shader complexity and level of detail based on the user's gaze direction, reducing processing workload by varying resolution and detail levels across the display, with higher detail in the foveal region and lower detail in peripheral areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If high-quality image content is provided across the entire display, then image quality is maintained, but processing resources are excessively consumed
Solution Approach 1:
The patent applies local quality by providing high-quality image content only in the foveal region where the user's gaze is directed, while supplying lower-quality content in peripheral regions. This resolves the contradiction by maintaining perceived image quality where it matters most to the user while significantly reducing overall processing resource consumption across the entire display.
Solution Approach 2:
The display is segmented into multiple regions based on gaze direction, with the foveal region identified and treated differently from peripheral regions. This segmentation allows the system to apply different quality levels to different parts of the display, optimizing the balance between image quality and processing resources.
2Measurement precision
If gaze tracking is performed using inwards-facing cameras in HMDs, then tracking accuracy is improved, but device complexity increases
Solution Approach 1:
The inwards-facing cameras in the HMD serve multiple functions: they capture the user's field of view for virtual reality rendering and simultaneously perform gaze tracking by analyzing eye position within the captured images. This multi-functionality reduces device complexity by eliminating the need for separate dedicated gaze tracking cameras while maintaining high tracking accuracy.
Data Source
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AI summary
An image rendering instruction generation system comprising an object identification unit operable to identify one or more objects for rendering in a virtual scene, a shader identification unit operable to identify a shader for rendering the identified objects, wherein the shader comprises two or more shading processes corresponding to different levels of detail, a draw call generation unit operable to generate a draw call comprising the identified shader, and a draw call output unit operable to provide the generated draw call to an image rendering system.