VR Display Distortion Measurement via Automated Corner Point Analysis
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Solution Overview
Problem
Current methods for measuring distortion parameters in Virtual Reality (VR) devices are time-consuming and labor-intensive, lacking accuracy due to reliance on manual fine-tuning and theoretical outputs, which do not effectively correct distortion in VR devices.
Innovation Solution
A method and apparatus that acquire and process distortion images by imaging an initial image through a lens, determining distortion parameters based on the locational relationship between corner points in the initial and distortion images, adjusting corner points until they satisfy a preset condition, and calculating distortion parameters using a processor and memory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual fine-tuning and theoretical outputs are used to measure distortion parameters, then the measurement process can be performed, but the measurement precision and productivity are poor due to being time-consuming and labor-intensive
Solution Approach 1:
The patent replaces manual fine-tuning operations with an automated image processing system. The controller automatically captures images through the lens, processes them to identify corner points, calculates distortion parameters using coordinate transformations, and generates correction data without human intervention. This substitutes the mechanical manual adjustment process with an automated optical-mechanical-electrical system.
Solution Approach 2:
The measurement system is self-sufficient, automatically performing all measurement tasks without external manual input. The controller autonomously captures images, processes corner point coordinates, calculates distortion parameters, and outputs correction data. The system serves itself by integrating image capture, processing, calculation, and output generation into a single automated workflow.
2Measurement precision
If corner points are adjusted to satisfy preset conditions through manual intervention, then measurement accuracy can be improved, but the device complexity and ease of operation deteriorate due to requiring artificial adjustments
Solution Approach 1:
The system implements feedback by capturing images through the lens, processing the images to identify corner point positions, comparing actual positions with expected positions, and using this information to calculate distortion parameters. The feedback loop continues until distortion parameters are accurately determined, automatically adjusting corner point coordinates through mathematical calculations rather than manual intervention.
Solution Approach 2:
The system changes parameters automatically by calculating new corner point coordinates based on distortion models. Instead of manually adjusting corner point positions, the controller computes transformed coordinates using distortion parameters, applying parameter transformations to achieve accurate corner point alignment and generate correction data.
3Ease of manufacture
If theoretical distortion parameters are used directly, then the measurement process is simple, but the reliability is poor because they do not effectively correct distortion in VR devices
Solution Approach 1:
The system performs preliminary actions by capturing actual images through the lens before calculating distortion parameters. Instead of directly using theoretical values, the system first obtains real image data, processes corner point coordinates from actual measurements, and then calculates distortion parameters based on empirical data. This preliminary image capture and processing ensures the parameters reflect actual device performance.
Solution Approach 2:
The system creates a copy of the actual optical path by capturing images through the lens and processing them to extract corner point information. This copying of the real measurement scenario allows calculation of distortion parameters that accurately represent the actual device behavior, rather than relying on theoretical models that may not match practice.
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
This approach eliminates the need for artificial adjustments, accurately calculating distortion parameters at multiple points, improving measurement efficiency and correction accuracy, thus enhancing the immersion experience in VR devices.
Implementation Method 1
a magnifying glass having a spherical radian to be installed in the virtual reality device
Data Source
AI summary
The present disclosure provides a method, apparatus, and measurement device for measuring distortion parameters of a display device, and a computer-readable medium. The display device includes a display screen and a lens located on a light exiting side of the display screen, and the method includes: acquiring a distortion image which is generated by imaging an initial image through the lens, wherein the initial image is an image displayed on the display screen, the initial image comprises a plurality of first corner points, and the distortion image comprises a plurality of second corner points which match the plurality of first corner points respectively; and determining the distortion parameters of the display device according to a locational relationship between the second corner points and a first corner points which match the second corner points.