MR Headset Depth-of-Field Correction Using User Feedback
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current optical see-through mixed reality (MR) head-mounted devices lack control indicators for depth of field rendering, failing to match the user's real visual experience.
Innovation Solution
A MR head-mounted device and system that employs a depth-of-field correction model, updating parameters based on user feedback signals to adjust the depth of field, using elements like convolutional neural networks and sensors to enhance the realism of virtual objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If depth of field rendering is controlled based on structured light and/or stereoscopic vision, then the depth of field effect can be presented, but it cannot match the user's real visual experience because there are no control indicators
Solution Approach 1:
The patent introduces a feedback mechanism by capturing user eye tracking data and using it to adjust depth of field parameters in real-time. The eye tracker monitors user gaze, and the system automatically adjusts the depth of field rendering based on where the user is looking, creating a closed-loop control system that adapts to user preferences without requiring manual input.
Solution Approach 2:
The system performs self-adjustment by automatically modifying depth of field parameters based on eye tracking data without requiring user intervention. The device serves itself by using its own sensor data (eye tracking) to control its rendering output, eliminating the need for external control indicators or manual adjustment by the user.
2Adaptability or versatility
If traditional depth of field control methods are used without user feedback, then the system structure remains simple, but the visual experience does not adapt to user focus changes in different scenes
Solution Approach 1:
The patent implements feedback by continuously monitoring user eye movements and using this information to dynamically adjust depth of field rendering. The eye tracker provides real-time feedback about user attention, allowing the system to adapt rendering parameters to match user focus changes across different scenes and viewing conditions.
Solution Approach 2:
The patent replaces manual or mechanical control mechanisms with an automated optical sensing system. Instead of using physical controls or complex mechanical adjustment mechanisms, the system uses eye tracking sensors and software-based processing to automatically adjust depth of field, substituting mechanical complexity with sensor-based automation.
Data Source
AI summary
A method of correcting depth of field, performed by a first MR head-mounted device, comprises: superimposing a first virtual object on a first background image to generate an superimposed image, inputting the superimposed image into a depth-of-field correction model to generate a displayed image and display the displayed image, receiving at least one user feedback signal corresponding to the displayed image, and updating a depth-of-field parameter of the depth-of-field correction model with the at least one user feedback signal for the depth-of-field correction model to generate an updated virtual object.