Eye Tracking Brightness Adjustment for Squinting
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Solution Overview
Problem
Eye tracking systems in head-mounted displays (HMDs) face accuracy issues due to squinting, which occludes light reflections and prevents reliable detection of eye glints, leading to errors in rendering images.
Innovation Solution
The system dynamically reduces the brightness of images presented to the user if squinting is detected, encouraging the user to open their eyes, thereby allowing accurate eye tracking to resume.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If the system maintains high brightness to provide good visual quality, then image quality is improved, but eye tracking accuracy deteriorates when the user squints
Solution Approach 1:
The patent applies dynamics by making the image brightness adjustable and responsive to real-time eye state detection. The system dynamically modifies brightness based on whether the eye is open or closed, transitioning between different brightness states to maintain both visual quality and tracking accuracy under varying conditions.
Solution Approach 2:
The system uses feedback from eye state detection (open/closed status) to control image brightness. The detector provides real-time information about eye state, and the controller adjusts brightness accordingly, creating a closed-loop system that adapts to user behavior to maintain tracking accuracy.
2Measurement precision
If the system reduces brightness to encourage the user to open their eyes, then eye tracking accuracy is improved, but visual quality deteriorates
Solution Approach 1:
The system applies periodic action by temporarily reducing brightness in response to detected eye-closed states, then restoring normal brightness when the eye opens. This periodic modulation of brightness encourages the user to open their eyes while maintaining good visual quality during normal operation.
Solution Approach 2:
The patent changes the brightness parameter dynamically based on eye state detection. By adjusting this physical parameter in response to detected conditions, the system maintains tracking accuracy without permanently degrading visual quality.
3Measurement precision
If the system continuously monitors eye state to maintain tracking accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system applies self-service by using the display device itself to generate the light reflections needed for tracking. The same display that presents images also creates the glints used for detection, eliminating the need for separate illumination sources and reducing overall system complexity.
Solution Approach 2:
The display device serves multiple functions: presenting visual content to the user and generating light reflections for eye tracking detection. This multi-functionality reduces the number of separate components needed, simplifying the system while maintaining tracking 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
This approach effectively reduces errors in eye tracking by encouraging the user to stop squinting, ensuring continuous and accurate tracking of eye movements, enhancing the performance of HMDs in applications like virtual reality.
Implementation Method 1
The glints are detected and can be used to interpret the position of the eye
Implementation Method 2
a system dynamically reduces the brightness of least a portion of one or more images presented to a user if the system detects the user squinting
Data Source
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AI summary
Embodiments generally relate to adjusting images for an eye tracking system. In some embodiments, a method includes presenting one or more images to a user. The method further includes obtaining gaze tracking data relating to a gaze of the user with respect to the one or more images presented to the user. The method further includes detecting one or more first gaze characteristics from the gaze tracking data, wherein the one or more first gaze characteristics indicate a first state of the gaze of the user. The method further includes reducing a brightness of at least a portion of the one or more images presented to the user based on the one or more first gaze characteristics.