Gaze-Based Imaging System for Head-Mounted Displays
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Solution Overview
Problem
Conventional imaging equipment and techniques are unsuitable for Head-Mounted Devices (HMDs), failing to produce truly gaze-contingent images due to hardware limitations, high framerate and resolution requirements, and difficulty in handling High-Dynamic-Range (HDR) and depth of field, leading to noise and motion blur issues.
Innovation Solution
An imaging system comprising a camera and a processor that adjusts camera attributes based on the user's gaze direction to capture realistic images, utilizing information about the object of interest to optimize camera settings for real-time or near-real-time image generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If video see-through camera arrangements are used to image the real-world environment, then the HMD can display images to the user, but the images are not truly gaze-contingent due to hardware limitations
Solution Approach 1:
The system pre-determines the object of interest based on predicted gaze direction before the user actually looks at it. This allows the imaging system to prepare and adjust camera settings in advance, ensuring that when the user gazes at an object, the image is already optimized for that specific gaze direction, achieving true gaze-contingency without hardware limitations
Solution Approach 2:
The system dynamically adjusts camera attributes (such as focus, exposure, and field of view) based on real-time or predicted gaze direction. This dynamic adaptation allows the imaging system to respond to changing gaze directions and maintain image quality across different viewing conditions, achieving both gaze-contingency and reliability
2Manufacturing precision
If high framerate and resolution are used to properly display images, then image quality is improved, but the technical capabilities of the video see-through camera arrangements are overwhelmed
Solution Approach 1:
Instead of maintaining high resolution across the entire field of view, the system applies high resolution and detailed imaging only to the local region of interest determined by gaze direction. Other regions can use lower resolution, reducing the overall computational and hardware burden while maintaining perceived image quality where the user is actually looking
Solution Approach 2:
The field of view is segmented into regions of interest and non-interest areas based on gaze direction. The imaging system processes and captures high-quality images only for the segmented region of interest, while other areas receive minimal processing, thereby reducing the complexity requirements of the camera arrangement
3Productivity
If advanced video see-through camera arrangements with high framerates and resolution are used, then image capture capability is improved, but depth of field and exposure requirements become too stringent, resulting in noisy, over-exposed or under-exposed images
Solution Approach 1:
The system pre-adjusts camera attributes such as exposure time, aperture, and gain based on the predicted object of interest and lighting conditions before capturing the image. This preliminary optimization ensures that when the high-framerate capture occurs, the exposure parameters are already tuned correctly, avoiding over or under-exposure and reducing noise
Solution Approach 2:
The system dynamically changes camera parameters (exposure time, aperture size, ISO sensitivity) based on the identified object of interest and scene lighting conditions. By adapting these parameters to the specific gaze-contingent scenario, the system maintains optimal exposure and image quality across varying lighting conditions while preserving high framerate capability
4Ease of operation
If conventional imaging equipment is used to capture the real-world environment, then the system is simple to operate, but the captured images are full of noise and moving objects are motion blurred beyond recognition
Solution Approach 1:
The system incorporates feedback loops that continuously monitor the captured images for quality metrics such as noise levels and motion blur. Based on this feedback, the system automatically adjusts camera settings including shutter speed, aperture, and gain to maintain optimal image clarity. This automated feedback-based adjustment eliminates the need for complex manual operation while preserving image quality
Data Source
AI summary
An imaging system for producing images for a display apparatus. The imaging system includes at least one camera, and processor communicably coupled to the at least one camera. The processor is configured to: obtain, from display apparatus, information indicative of current gaze direction of a user; determine, based on current gaze direction of the user, an object of interest within at least one display image, wherein the at least one display image is representative of a current view presented to user via display apparatus; adjust, based on a plurality of object attributes of the object of interest, a plurality of camera attributes of the at least one camera for capturing a given image of a given real-world scene; and generate from the given image a view to be presented to user via display apparatus.