Eye Tracker Component Placement Optimization for Wearables
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Solution Overview
Problem
Existing eye trackers on wearable devices face challenges in maintaining accuracy across a wide range of users due to varying head and facial features, making it difficult to determine the optimal position and placement of eye tracker components for effective eye movement tracking.
Innovation Solution
A wearable device design system that uses 3D models of heads and wearable devices to simulate the placement of eye tracker components, including sensors and light sources, to generate performance data and optimize their positioning for improved accuracy across multiple users, adjusting parameters such as viewing angles and synthetic eye features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If eye tracker components are positioned on a wearable device for a specific user, then tracking accuracy for that user is improved, but adaptability to other users with different facial features deteriorates
Solution Approach 1:
The system changes the parameters of the eye tracker component positioning by calculating optimal positions based on each user's specific facial geometry parameters (distances between eyes, nose, ears, and chin). This allows the same eye tracker hardware to be accurately positioned for different users by adjusting its spatial parameters rather than using a fixed position
Solution Approach 2:
The system performs preliminary measurement and calculation of facial features before positioning the eye tracker. By pre-capturing the user's facial geometry and computing the optimal component positions in advance, the system ensures accurate tracking is established before actual eye movement monitoring begins
2Reliability
If the wearable device is customized for each individual user, then tracking performance is improved, but device complexity and manufacturing difficulty increase
Solution Approach 1:
The system creates a digital 3D model (copy) of the user's facial geometry through image capture and processing. This virtual replica allows the system to simulate and determine optimal eye tracker positioning without physically customizing the device for each user, thereby maintaining simplicity in manufacturing while achieving personalized fit
3Measurement precision
If the eye tracker components are positioned to maximize visibility of the eye, then tracking accuracy is improved, but the difficulty of determining optimal position increases
Solution Approach 1:
The system replaces manual or trial-and-error mechanical positioning with an automated computational approach. By using image processing algorithms and geometric calculations based on captured facial features, the system automatically determines the optimal position and orientation of eye tracker components without requiring physical adjustment or subjective assessment
Data Source
AI summary
According to an aspect, a method for designing an eye tracker on a wearable device includes selecting a first three-dimensional (3D) model of at least a head of a person, selecting a second 3D model of a wearable device, positioning a synthetic eye within the first 3D model, positioning an eye tracker component at a first location on the second 3D model, the eye tracker component including at least one of an eye tracker sensor or a light source, moving at least one of the first 3D model or the second 3D model such that at least a portion of the first 3D model contacts at least a portion of the second 3D model, and generating performance data with the eye tracker component positioned at the first location on the second 3D model.