Facial Parameter Analysis for Adaptive Display Brightness
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Solution Overview
Problem
Conventional display systems fail to account for individual user factors, such as visual acuity, leading to varying user experiences in viewing content, especially in varying lighting conditions, and do not adapt display settings accordingly.
Innovation Solution
A method and apparatus that capture images of the user to obtain facial parameters related to visual acuity, determine if the user is experiencing difficulty in resolving content, and adjust display settings such as text size, brightness, or contrast based on these parameters and historical data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If display brightness is increased to ensure high contrast in bright conditions, then visibility is improved, but individual user visual acuity differences are not addressed
Solution Approach 1:
The system transitions from uniform display settings for all users to personalized display parameters tailored to each user's visual acuity. By capturing facial images and analyzing eye-related parameters, the system determines individual visual acuity scores and adjusts display brightness, contrast, and text size locally for each user, thereby addressing individual visual needs while maintaining overall system functionality
Solution Approach 2:
The display settings become dynamic and adaptable rather than static. The system continuously monitors user facial parameters and automatically adjusts display characteristics in real-time based on detected visual acuity changes. This dynamic adaptation allows the display to respond to individual user needs without requiring manual intervention, resolving the contradiction between fixed brightness settings and individual adaptability
2Adaptability or versatility
If conventional systems use ambient light sensors to adapt display brightness, then lighting condition adaptation is achieved, but individual user factors are not taken into account
Solution Approach 1:
The system merges two previously separate adaptation mechanisms: ambient light sensing and individual user characteristics. By combining environmental lighting data with user-specific facial parameter analysis, the system creates a comprehensive adaptation model that simultaneously considers both external conditions and individual user factors, thereby preventing loss of individual user information while maintaining lighting adaptation capabilities
Solution Approach 2:
The system implements a feedback loop where user facial parameters are continuously captured and analyzed to determine visual acuity scores. This feedback mechanism allows the system to learn and adapt to individual user characteristics over time, ensuring that individual user information is preserved and utilized for personalized display optimization while maintaining responsiveness to lighting conditions
Data Source
AI summary
A method to determine whether a user is experiencing difficulty visually resolving content is disclosed. The method includes capturing one or more images of the user while the user is viewing the content. The method also includes obtaining facial parameters related to a visual acuity of the user from the captured one or more images. The method further includes determining whether the user is experiencing difficulty visually resolving the content based on the obtained one or more facial parameters. The method is implemented in a device such as a smartphone, tablet computer, or television. The facial parameters include information about the extent to which the user has their eyes open or closed, whether the user is wearing glasses, and the distance at which the user is viewing the content.