Gaze-Based Exposure for Mixed Reality HDR Imaging
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Solution Overview
Problem
Current mixed and augmented reality systems face challenges in providing an optimal exposure experience, as existing auto-exposure methods can result in image quality issues due to exposure variations across the scene, leading to artifacts in peripheral areas and loss of detail.
Innovation Solution
A gaze-based exposure method is implemented in MR systems, where the camera exposure is adjusted based on the user's gaze direction, using selective auto-exposure for a region of interest and ambient lighting information to generate exposure-compensated, foveated high dynamic range (HDR) images, preserving detail and minimizing exposure artifacts in peripheral areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If auto-exposure is applied to the entire scene, then overall image brightness is balanced, but image quality deteriorates due to exposure artifacts in peripheral areas and loss of detail
Solution Approach 1:
The patent applies different exposure strategies to different regions of the image: the foveal region (center) uses auto-exposure optimized for the region of interest, while peripheral regions use exposure compensation based on ambient lighting. This local differentiation allows each region to have optimal exposure characteristics, resolving the contradiction between overall brightness balance and local image quality.
2Manufacturing precision
If exposure is optimized for the region of interest, then detail in the gaze area is preserved, but peripheral areas exhibit exposure artifacts
Solution Approach 1:
The system applies local quality by treating the foveal and peripheral regions differently. The foveal region receives full auto-exposure optimization for maximum detail preservation, while peripheral regions receive exposure compensation that prevents artifacts. This spatially differentiated approach resolves the contradiction between localized detail preservation and peripheral quality.
Solution Approach 2:
The patent introduces an intermediary exposure compensation mechanism that mediates between the auto-exposed foveal region and the display requirements. By applying exposure compensation to peripheral regions based on ambient lighting information, the system acts as a mediator that prevents harmful exposure artifacts while maintaining the benefits of ROI-optimized exposure.
3Illumination intensity
If multiple exposures are captured for HDR, then dynamic range is improved, but processing complexity and time increase
Solution Approach 1:
The patent extracts and utilizes only the most essential exposure information needed for HDR效果 - specifically, ambient lighting information from the scene. Instead of capturing and processing multiple full exposures, the system extracts key exposure parameters and applies them through compensation, significantly reducing processing complexity while maintaining HDR benefits.
Solution Approach 2:
The system changes the approach from capturing multiple exposure images to modifying exposure parameters (brightness/contrast) through computational compensation. By changing from a spatial/temporal sampling approach (multiple images) to a parameter adjustment approach (exposure compensation), the system achieves HDR效果 with reduced complexity.
Data Source
AI summary
A processing pipeline and method for mixed reality systems that utilizes selective auto-exposure for a region of interest in a scene based on gaze and that compensates exposure for the rest of the scene based on ambient lighting information for the scene. Images may be generated for display that provide an exposure-compensated, foveated high dynamic range (HDR) experience for the user.