Gaze-Based Camera Exposure Control for ROI Brightness Stability
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Solution Overview
Problem
Existing automatic exposure control (AEC) algorithms in artificial reality systems fail to optimize image brightness for a user's region of interest, often leading to over-exposed or under-exposed regions that obscure the user's preferred areas of view.
Innovation Solution
A gaze-based automatic exposure control (AEC) algorithm that identifies the user's region of interest (ROI) using eye tracking techniques and adjusts camera exposure dynamically to ensure optimal visibility of that region, incorporating temporal filtering to stabilize exposure changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If traditional automatic exposure control (AEC) algorithms adjust exposure based on overall image brightness, then the general visibility of the scene is improved, but the user's region of interest (ROI) becomes over-exposed or under-exposed and obscured
Solution Approach 1:
The patent divides the image into multiple regions including the user's region of interest (ROI) and other areas. The AEC algorithm then calculates exposure values for each region separately using different weighting factors, allowing the ROI to be optimized independently from the rest of the scene. This segmentation enables the system to prevent over-exposure or under-exposure in the user's preferred viewing area while maintaining acceptable brightness elsewhere.
Solution Approach 2:
The patent applies different exposure control strategies to different parts of the image. Specifically, the ROI receives specialized exposure treatment with higher weighting to ensure optimal visibility, while other regions use standard or reduced weighting. This local quality approach ensures that the user's region of interest achieves precise exposure accuracy without requiring the entire image to be uniformly optimized.
2Manufacturing precision
If the camera exposure is adjusted to optimize the user's region of interest, then the visibility of the preferred area is improved, but other regions of the image may become over-exposed or under-exposed
Solution Approach 1:
The patent implements a dynamic exposure control system that continuously adapts exposure parameters based on real-time detection of the user's region of interest. The system dynamically adjusts weighting factors and exposure values frame-by-frame, allowing the ROI to maintain optimal visibility even as the user's gaze moves. This dynamic approach balances the need for precise ROI exposure with maintaining acceptable brightness in other regions through continuous optimization.
Solution Approach 2:
The system uses feedback from eye-tracking or user interaction data to continuously monitor which region the user is viewing. This feedback informs the AEC algorithm to adjust exposure parameters specifically for that region while applying reduced weighting to other areas. The feedback mechanism ensures that the ROI receives prioritized exposure control without completely sacrificing the visibility of surrounding regions.
3Illumination intensity
If the exposure control prioritizes the center field of view, then the central region visibility is improved, but the user's actual region of interest which may be off-center becomes obscured
Solution Approach 1:
The patent performs preliminary detection of the user's region of interest using eye-tracking or interaction data before the exposure control is applied. By identifying the ROI in advance, the system can pre-calculate appropriate weighting factors and exposure parameters specifically for that region, rather than relying on fixed center-weighted exposure. This preliminary action ensures that the exposure control is tailored to the user's actual viewing area, whether central or off-center.
Solution Approach 2:
The system dynamically changes exposure parameters including weighting factors and exposure values based on the detected region of interest. When the user's ROI is off-center, the algorithm adjusts the spatial distribution of weighting factors to prioritize that specific area rather than the image center. This parameter change capability allows the system to adapt exposure control to any region the user is viewing, not just the center field of view.
Data Source
AI summary
In one embodiment, a method includes receiving a user's eye gaze and using the eye gaze to determine a point of interest. The method further includes determining a current region of interest based on the point of interest, determining a temporal stability of the eye gaze by comparing the current region of interest to a past region of interest, and assigning a weight to the region of interest. The method further includes using the weight and region of interest to compute an exposure control parameter, and instructing a camera to capture an image with the exposure control parameter.