Adaptive VST XR IPD Estimation Using Reference Object Projection
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Solution Overview
Problem
Existing XR systems face challenges in accurately determining interpupillary distance (IPD) without specialized equipment like a pupilometer, which is not readily accessible to users, hindering personalized device configuration and image rendering.
Innovation Solution
Utilizing a method to estimate IPD by capturing images of a user's face and a reference object with known dimensions, identifying planes for the eyes and object, projecting the object's image data onto the eye plane, and calculating IPD based on pixel spacing and object dimensions, potentially verified through depth estimation and image rectification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If specialized equipment like a pupilometer is used to measure interpupillary distance, then measurement precision is improved, but device complexity and accessibility worsen
Solution Approach 1:
The patent uses a virtual copy of the reference object (projected image data) instead of physical measurement tools. By projecting the reference object onto the eye plane and measuring pixel distances in the image, the system creates a virtual measurement model that replaces the need for physical pupilometers while maintaining measurement accuracy.
Solution Approach 2:
The patent introduces a reference object as an intermediary element between the camera and the eyes. This reference object with known dimensions serves as a mediator to establish a scaling factor that converts pixel measurements into real-world distances, enabling accurate IPD measurement using ordinary cameras instead of specialized equipment.
2Measurement precision
If a reference object with known dimensions is projected onto the eye plane, then measurement precision is improved, but processing complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-identifying the eye plane and pre-projecting the reference object onto this plane before measuring the interpupillary distance. This sequence of preparatory steps establishes the measurement framework in advance, making the actual IPD measurement process more straightforward and accurate.
Solution Approach 2:
The system creates a virtual copy of the reference object by projecting its image data onto the eye plane. This projected copy maintains the known dimensions of the reference object in the virtual space, allowing accurate pixel-to-real-world conversions without requiring complex physical measurement setups.
3Ease of operation
If pixel spacing is used to estimate interpupillary distance, then ease of operation is improved, but measurement precision worsens
Solution Approach 1:
The patent introduces a reference object as an intermediary that bridges the gap between simple pixel counting and accurate real-world measurement. By knowing the reference object's actual dimensions and its projected pixel size, the system can convert simple pixel measurements into precise real-world distances through a calculated scaling factor.
Solution Approach 2:
The system changes the parameter from raw pixel spacing to a scaled distance measurement. By applying the scaling factor derived from the reference object's known dimensions and projected pixel count, the system transforms simple pixel-based measurements into accurate real-world IPD measurements, effectively changing the measurement parameter while maintaining operational simplicity.
Data Source
AI summary
A method includes obtaining one or more images capturing a face of a user and a reference object with one or more known dimensions. The method also includes identifying a first plane on which eyes of the user are located and a second plane on which the reference object is located and projecting image data of the reference object from the second plane onto the first plane. The method further includes determining a sizing factor based on pixels that the reference object occupies after being projected onto the first plane and the known dimension(s). The method also includes identifying a number of pixels between centers of pupils of the user's eyes in the image(s). In addition, the method includes identifying an estimate of an interpupillary distance of the user's eyes by applying the sizing factor to the number of pixels between the centers of the pupils of the user's eyes.