Head-Mounted Display Personalization via User Data Retrieval
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Solution Overview
Problem
Current multimedia systems with head-mounted devices (HMDs) lack personalized adjustments for user-specific factors such as interpupillary distance, diopter values, color blindness, and user habits, leading to suboptimal virtual environment experiences due to picture distortions and inefficient resource utilization.
Innovation Solution
A method and system that retrieves human factor data from storage, radio signals, or images to automatically adjust the HMD's software and hardware components, including display positions, lens movements, color renderings, and camera settings based on user-specific data like IPD, diopter values, color blindness type, and usage habits, ensuring optimal immersion and resource efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the HMD uses fixed display settings for all users, then the device complexity is reduced, but the picture distortion increases for users with different interpupillary distances
Solution Approach 1:
The display settings are made dynamically adjustable based on retrieved user data. The system automatically modifies display parameters such as interpupillary distance and diopter values according to the specific user, transforming fixed settings into adaptive, user-specific configurations that eliminate picture distortion without requiring complex manual adjustment mechanisms
Solution Approach 2:
The system changes display parameters (interpupillary distance, diopter values, color rendering settings) based on retrieved user-specific data. By automatically adjusting these parameters for each user, the system resolves picture distortion issues while keeping the device structure simple, as the changes are implemented through software configuration rather than hardware modification
2Adaptability or versatility
If the HMD provides personalized adjustments for each user, then the user experience is improved, but the device complexity increases
Solution Approach 1:
The system automatically retrieves user-specific data and performs self-adjustment of display parameters without requiring manual user input or complex interaction. The HMD autonomously configures interpupillary distance, diopter values, and other settings based on retrieved data, providing personalized adaptation while minimizing the complexity of user-facing controls and interfaces
Solution Approach 2:
User-specific data including interpupillary distance, diopter values, and color blindness information is retrieved and processed in advance before the user begins using the HMD. This preliminary configuration allows the system to be pre-adapted to each user's needs, eliminating the need for complex real-time adjustments during operation and reducing the perceived complexity for the user
3Adaptability or versatility
If the multimedia system processes multiple user data types, then the adaptability is improved, but the power consumption increases
Solution Approach 1:
The system extracts and processes only the specific user data types that are actually needed for optimization (such as interpupillary distance, diopter values, and color blindness information). By selectively retrieving and processing relevant data rather than all possible user data, the system achieves adaptability while minimizing unnecessary computational overhead and power consumption
Solution Approach 2:
The system processes user data to the extent necessary for achieving optimal display configuration, without performing excessive or redundant processing. By focusing computational resources on the essential parameters needed for personalization (interpupillary distance, diopter, color rendering), the system achieves sufficient adaptability while avoiding the increased power consumption that would result from processing all possible user data types
Data Source
AI summary
A driving method, suitable for a multimedia system including a head-mounted device (HMD), includes the following operations: retrieving human factor data from a storage device, a radio signal, or an image; and according to the human factor data, automatically adjusting software for driving the HMD or hardware components of the multimedia system.