Eye Openness Detection Using Pixel Intensity Thresholds
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Solution Overview
Problem
Existing eye tracking systems in wearable devices face challenges in accurately determining eye openness and positioning lenses for optimal viewing, especially in varying eye shapes and sizes, which affects the immersive experience in VR and AR applications.
Innovation Solution
The system employs an eye tracking device with an image sensor and infrared illuminator to capture images of the eye, analyzing pixel intensity and reflection patterns to determine eye openness and adjust lens positioning based on threshold values, ensuring the eye is optimally aligned with the lens for improved immersion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing eye tracking systems use standard image processing methods to determine eye openness, then the system structure remains simple, but measurement precision deteriorates due to varying eye shapes and sizes
Solution Approach 1:
The patent transforms the eye openness detection problem from direct pixel intensity analysis to a parameter-based approach. It extracts geometric parameters (eye contour, pupil position, eyelid boundaries) and uses normalized coordinate systems to account for varying eye shapes and sizes. This parameter transformation enables accurate measurement across different users without requiring complex adaptive algorithms for each individual case.
Solution Approach 2:
The system performs preliminary actions by pre-defining anatomical reference points and standardization procedures for eye structure analysis. It establishes baseline parameters for eye contours, pupil positions, and eyelid boundaries before actual measurement, allowing the system to adapt to different eye geometries using standardized transformation routines rather than requiring complex real-time adaptation.
2Measurement precision
If the system uses detailed image analysis to accurately determine eye position and openness, then measurement precision improves, but processing time increases
Solution Approach 1:
The patent segments the eye image analysis into distinct functional regions: outer eye contour detection, pupil boundary identification, and eyelid position determination. Each segment is processed independently using optimized algorithms appropriate for that specific feature, reducing overall processing time compared to analyzing the entire image uniformly. The segmentation allows parallel processing of different eye features.
Solution Approach 2:
The system extracts only the essential geometric features needed for eye tracking (contour points, pupil center, eyelid boundaries) from the full eye image, discarding redundant information. This extraction approach focuses computational resources on critical measurement points rather than processing every pixel, significantly reducing processing time while maintaining measurement precision.
3Adaptability or versatility
If the system implements comprehensive eye tracking analysis to ensure optimal lens alignment, then the immersive experience improves, but device complexity increases
Solution Approach 1:
The patent implements a universal eye analysis framework that handles various eye shapes, sizes, and anatomical variations through standardized geometric modeling. The same core algorithms and parameter extraction methods work across different users and eye types, providing multi-functional adaptability without requiring separate specialized processing paths for each eye geometry type.
Solution Approach 2:
The system uses parameter transformation and normalization to adapt to different eye geometries. By expressing eye features in normalized coordinate systems and using scaling factors, the system maintains consistent processing logic across diverse eye shapes and sizes, achieving versatility through mathematical parameter adjustments rather than structural system changes.
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 provides accurate eye openness detection and adjusts lens positioning, enhancing the immersive experience by ensuring optimal eye-lens alignment, accommodating different eye shapes and sizes, and improving the overall performance of VR and AR applications.
Implementation Method 1
an eye tracking device with an image sensor and infrared illuminator to capture images of the eye
Implementation Method 2
image sensor and infrared illuminator to capture images
Data Source
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AI summary
A method for determining eye openness with an eye tracking device is disclosed. The method may include determining, for pixels of an image sensor of an eye tracking device, during a first time period when an eye of a user is open, a first sum of intensity of the pixels. The method may also include determining, during a second time period when the eye of the user is closed, a second sum of intensity of the pixels. The method may further include determining, during a third time period, a third sum of intensity of the pixels. The method may additionally include determining that upon the third sum exceeding a fourth sum of the first sum plus a threshold amount, that the eye of the user is closed, the threshold amount is equal to a product of a threshold fraction and a difference between the first sum and the second sum.