Camera Positioning for VR Eye Tracking via Ratio-Based Algorithm
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Solution Overview
Problem
Current camera positioning methods in video display technology, particularly in virtual reality eyewear, are laborious and inefficient, leading to inaccurate eye tracking due to difficulties in determining the optimal camera position and shooting angle, resulting in incomplete or low-quality eye image capture.
Innovation Solution
A camera positioning method that determines positioning configuration information, including distance limitation data, target data, and camera parameter data, using a preset algorithm to calculate the camera's position and shooting angle, ensuring the human eye occupies a suitable ratio within the image frame, typically between 1/3 to 2/3, to improve recognition accuracy and adjust camera settings accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the camera is too far away from the human eye, then the shooting range is sufficient, but the human eye occupies a small proportion of the acquired image leading to low recognition accuracy
Solution Approach 1:
The patent calculates and adjusts the camera distance parameter based on the desired eye image ratio. By changing the distance parameter to a specific range (1/3 to 2/3 of the image frame), the system achieves optimal eye recognition accuracy while maintaining sufficient shooting range.
2Measurement precision
If the camera is too close to the human eye, then the human eye occupies a large proportion of the acquired image, but the human eye may exceed the shooting range when there is a small displacement
Solution Approach 1:
The patent establishes a specific parameter range for camera distance (1/3 to 2/3 of the image frame) that balances eye recognition accuracy with tracking reliability. This parameter optimization ensures the eye remains within the shooting range even during small displacements.
3Manufacturing precision
If multiple simulation tests are used for camera positioning, then the positioning can be performed, but the process is laborious and inefficient
Solution Approach 1:
The patent replaces the mechanical simulation test process with a mathematical calculation method. By using geometric relationships and trigonometric formulas to calculate camera positioning parameters directly, the system eliminates the need for repeated physical testing while maintaining positioning accuracy.
Solution Approach 2:
The patent creates a mathematical model that copies the essential geometric relationships of the camera-eye-display system. By solving the mathematical equations derived from the geometric model, the system obtains positioning results without physically replicating multiple test scenarios.
4Ease of manufacture
If the camera positioning is not optimized, then the setup is simple, but the eye image ratio is inappropriate affecting recognition and tracking
Solution Approach 1:
The patent provides a straightforward parameter adjustment method where the camera distance is set to a specific ratio (1/3 to 2/3 of the image frame). This simple parameter change achieves optimal eye image composition without complicating the overall setup process.
Data Source
AI summary
A camera positioning method, device and medium are provided. The method includes: determining positioning configuration information; determining, according to the positioning configuration information, positioning information of the camera by a preset algorithm, the positioning information including distance limitation data which defines a distance between a target and the camera; and determining a position of the camera according to the positioning information, wherein the positioning configuration information includes target data, ratio data of a target image in an image captured by the camera, and camera parameter data.