Dynamic Visual Content Adaptation for Color Blindness
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current visual content, such as images and videos, does not account for users with visual impairments like color blindness, preventing them from fully appreciating the content, and there is no means to dynamically modify this content to accommodate such impairments.
Innovation Solution
A system and method that uses generative adversarial networks to apply personalized style transfers to visual content templates based on user responses to visual impairment tests, generating customized content that is easier to distinguish for users with color blindness, involving a processor, server, and content generator to query databases and apply style transfers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If visual content is generated with standard color palettes, then the content is visually appealing to users with normal color vision, but users with color blindness cannot distinguish certain colors and fully appreciate the content
Solution Approach 1:
The system dynamically adjusts color palettes in visual content based on real-time detection of the user's color vision type. Instead of creating static content for each user type, the system modifies colors on-the-fly using generative adversarial networks, allowing a single content generation system to serve all users with different visual capabilities.
Solution Approach 2:
The system changes the color parameters of visual content based on the detected color vision type of the user. By detecting whether a user has normal color vision, deuteranopia, protanopia, tritanopia, or other color vision deficiencies, the system transforms the color palette parameters to ensure distinguishability while maintaining visual appeal.
2Ease of manufacture
If visual content is created without considering color blindness, then the content generation process is simple and efficient, but there is no means to modify the content to account for visual impairments
Solution Approach 1:
The system performs preliminary detection of the user's color vision type before generating or displaying visual content. By detecting the user's visual capabilities in advance, the system can pre-adjust the color palette parameters, ensuring that the content is automatically optimized for the user's specific needs without requiring manual intervention.
Solution Approach 2:
The system introduces an intermediary color transformation layer between the standard visual content and the user's display. This intermediary layer uses generative adversarial networks to translate standard colors into color palettes that are distinguishable for users with various color vision deficiencies, while preserving the original content's visual appeal and meaning.
3Productivity
If standard color palettes are used in visual content, then the content creation process is straightforward, but people with color blindness are unable to distinguish certain colors
Solution Approach 1:
The system uses feedback from color blindness detection tests to automatically adjust color palettes. By having users complete brief detection tests, the system receives feedback about their specific color vision type and uses this information to transform colors in real-time, ensuring that color distinction information is preserved for each user type without requiring manual content creation for each scenario.
Data Source
AI summary
Systems and methods of dynamically modifying visual content to account for user visual impairments are provided. The systems and methods provide for a plurality of generative adversarial networks, each associated with a corresponding style transfer, wherein the style transfer uniquely transforms the color mapping of a content template based on responses to at least one visual impairment test.