Image Adjustment Based on Pupil Size and Gaze Angle
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Solution Overview
Problem
Display systems, particularly in augmented and virtual reality, face issues with image distortions due to variations in pupil size and gaze angle, leading to non-uniform image presentation that affects user perception.
Innovation Solution
A system that uses eye tracking to determine pupil size and gaze angle, generating an intensity map to adjust the red, green, and blue intensity values of the image, allowing for real-time correction of image imperfections by interpolating between pre-configured intensity maps based on pupil size and gaze angle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the display presents an image with fixed intensity values, then the device complexity is low, but the image quality and uniformity deteriorate due to pupil size variations
Solution Approach 1:
The system pre-calculates and stores multiple intensity maps corresponding to different pupil sizes before actual use. When the user views the display, the system simply selects the appropriate pre-computed intensity map based on detected pupil size, avoiding real-time complex calculations and achieving high image quality without requiring complex real-time processing hardware
Solution Approach 2:
The system adjusts the intensity values of red, green, and blue pixels based on the detected pupil size by selecting from pre-configured intensity maps. This parameter adjustment compensates for the optical effects of different pupil sizes, thereby improving image quality and uniformity without adding physical hardware complexity
2Measurement precision
If the system uses eye tracking to detect pupil size in real-time, then the image adjustment accuracy improves, but the loss of time increases due to continuous detection and processing
Solution Approach 1:
The system performs the time-consuming intensity map selection and image adjustment process in advance by pre-computing multiple intensity maps for different pupil sizes. During actual use, only lightweight pupil size detection and map selection are needed, significantly reducing real-time processing time while maintaining high measurement precision
Solution Approach 2:
The system dynamically adjusts the image intensity based on the detected pupil size by selecting from a set of pre-configured intensity maps. This dynamic adaptation allows the system to respond to changing pupil sizes in real-time without requiring continuous complex calculations, thus balancing measurement precision with processing efficiency
3Manufacturing precision
If the display adjusts intensity values for each pixel based on pupil size, then the image uniformity improves, but the use of energy increases due to additional processing
Solution Approach 1:
The system pre-computes and stores multiple intensity maps corresponding to different pupil sizes before actual use. During operation, it simply selects the appropriate pre-computed map based on detected pupil size, avoiding energy-intensive real-time calculations while achieving uniform image quality across different viewing conditions
Solution Approach 2:
The system adjusts pixel intensity parameters by selecting from pre-configured intensity maps based on detected pupil size. This parameter-based adjustment approach achieves uniform image presentation across different pupil sizes without requiring energy-intensive real-time image processing algorithms
Data Source
AI summary
Systems and methods for adjusting an image based on pupil size are disclosed. Particularly, a system for adjusting an image being presented on a display includes a processor. The processor is configured to identify a size of a pupil of a user viewing an image presented on the display, determine an intensity map based at least on the size of the pupil, and adjust the intensity values of at least a portion of the image using the intensity map. The intensity map indicates an amount of adjustment to intensity values of at least a portion of the image being displayed.