Two-Eye Gaze Point Fusion Using Independent Eye Mapping
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Solution Overview
Problem
Conventional methods for determining a two-eye gaze point rely on a fused ray from the user's eyes, failing to account for individual eye gaze points, which limits precision in immersive reality experiences.
Innovation Solution
A method and host system that independently determine and combine first and second gaze points from each eye on a reference plane, using a weighted combination to calculate a two-eye gaze point, incorporating image recognition and machine learning for enhanced accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a fused ray method is used to determine two-eye gaze point, then the calculation process is simplified, but the measurement precision of gaze point determination deteriorates
Solution Approach 1:
The patent segments the gaze determination process into independent eye-level calculations. Instead of calculating a fused ray from both eyes simultaneously, the system separately determines gaze points for the left eye and right eye independently, then combines these segmented results to achieve higher precision while maintaining manageable computational complexity
Solution Approach 2:
The patent introduces a new dimensional approach by calculating gaze points at multiple eye levels (left eye level and right eye level) separately before combining them. This multi-level dimensional strategy allows the system to capture nuanced gaze information that a single fused ray would miss, thereby improving measurement precision
2Measurement precision
If individual eye gaze points are considered separately, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent divides the complex task of determining two-eye gaze point into segmented, manageable steps: first determining left-eye gaze point independently, then right-eye gaze point independently, and finally combining these results. This segmentation reduces the apparent complexity by breaking down the problem into smaller, solvable units
Solution Approach 2:
The patent merges the separately calculated eye-level gaze points through a systematic combination process. By integrating the left-eye and right-eye gaze determination results in a structured manner, the system achieves high precision without overwhelming computational complexity, as the merging step builds upon previously computed intermediate results
Data Source
AI summary
The embodiments of the disclosure provide a method for determining a two-eye gaze point and a host. The method includes: obtaining a first gaze point of a first eye on a reference plane and obtaining a second gaze point of a second eye on the reference plane; and determining a two-eye gaze point via combining the first gaze point and the second gaze point.