Eye Enrollment in Head-Mounted Enclosures for Distortion Calibration
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Solution Overview
Problem
Head-mounted displays often suffer from image distortion due to variations in user facial geometries and eye positions, leading to inaccurate image presentation and impaired stereoscopic vision, with manual calibration methods being cumbersome and error-prone.
Innovation Solution
An eye enrollment process using image sensors and computer vision techniques to determine the positions of a user's eyes relative to the head-mounted enclosure, enabling accurate calibration of image presentation systems through three-dimensional transformations and distortion maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual adjustments of head-mounted display shape are made to mitigate distortion, then image quality can be improved, but device complexity and ease of operation deteriorate
Solution Approach 1:
The system performs automatic eye position detection and calibration without requiring manual user adjustments. The image sensor captures images of the user's eyes, and the processing apparatus automatically determines eye positions and calculates transformation parameters, eliminating the need for complex manual shape adjustments while maintaining high image quality
Solution Approach 2:
The patent replaces manual mechanical adjustment mechanisms with an automated optical-digital system. Instead of physically adjusting the head-mounted display shape through mechanical means, the system uses image sensors to capture eye positions and applies digital three-dimensional transformations to correct distortion, thereby reducing device complexity and improving ease of operation
2Reliability
If manual calibration methods are used to align image presentation with user eye positions, then stereoscopic vision can be improved, but ease of operation deteriorates
Solution Approach 1:
The calibration process is fully automated through eye position detection. The system captures images of the user's eyes using an image sensor, automatically detects eye positions, and calculates the necessary transformation parameters without requiring the user to perform any calibration actions, making the process simple and error-free while ensuring accurate stereoscopic vision
Solution Approach 2:
The system uses real-time feedback from image sensors that detect eye positions and gaze directions. This feedback is processed to automatically adjust the image presentation parameters, ensuring accurate alignment with the user's actual eye positions and improving stereoscopic vision without manual intervention
3Measurement precision
If eye position detection accuracy is improved through detailed image processing, then image presentation quality can be improved, but device complexity deteriorates
Solution Approach 1:
The patent extracts only the essential information needed for calibration by detecting specific features in the captured images, such as eye positions and pupil centers. Rather than performing complex full-image analysis, the system focuses on extracting key geometric parameters from the images, thereby achieving high measurement precision while keeping the processing complexity manageable
Solution Approach 2:
The system performs preliminary image capture and processing during a brief enrollment phase before actual use. During this preliminary action, the eye positions are detected and stored for subsequent image presentation adjustments. This preliminary detection eliminates the need for continuous complex processing during normal operation, reducing overall device complexity while maintaining high accuracy
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Improves the quality of computer-generated reality experiences by accurately aligning virtual objects with user eye positions, enhancing image perception and stereoscopic vision without the need for complex eye tracking systems.
Implementation Method 1
capturing a set of images that depict one or more eyes of a user via reflection in an optical assembly of a head-mounted enclosure
Data Source
AI summary
Systems and methods for eye enrollment for a head-mounted enclosure are described. Some implementations may include an image sensor; and a processing apparatus configured to: access a set of images, captured using the image sensor, that depict a face of a user and a head-mounted enclosure that the user is wearing; and determine, based on the set of images, a first position of a first eye of the user relative to the head-mounted enclosure.