Personalized Content Gradients From Image Key Color Extraction
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Solution Overview
Problem
Existing online social media platforms lack the ability to automatically generate visually appealing and personalized non-video content that complements user-generated images, often resulting in blank spaces or unsatisfactory visual experiences.
Innovation Solution
The system identifies key colors from a user's image, converts them to a wide gamut color space like OKLCH, and generates a gradient background to enhance the user-generated content, such as text or audio, ensuring aesthetic alignment with the image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If automatic gradient generation is implemented, then visual appeal and personalization are improved, but system complexity increases
Solution Approach 1:
The system automatically extracts key colors from user images and generates complementary gradients without requiring user input or manual selection. The gradient generation process is self-service, taking the image as input and producing the optimized background automatically, thereby improving ease of manufacture while managing complexity through automation.
Solution Approach 2:
The patent replaces manual gradient creation (mechanical/systematic manual process) with automated image processing and color analysis algorithms. By substituting the manual mechanical process with computational image analysis and automatic gradient synthesis, the system achieves ease of manufacture while the complexity is contained within the automated processing pipeline.
2Manufacturing precision
If wide gamut color spaces like OKLCH are used, then color accuracy and visual richness are improved, but processing complexity increases
Solution Approach 1:
The patent transforms color representation from standard RGB spaces to wide gamut OKLCH color spaces, changing the parameter system used for color definition. This parameter change enables more accurate and visually rich color representation. The complexity increase is managed by implementing the transformation within the automated processing pipeline, where the system handles the coordinate conversion and gradient synthesis in the new color space.
3Adaptability or versatility
If personalized gradients are generated for each user, then user experience is improved, but processing time and resources increase
Solution Approach 1:
The system performs preliminary color extraction and gradient generation as part of the automated content creation process. By pre-processing the image to extract key colors and pre-generating the gradient background before final content assembly, the system achieves personalization while managing processing time through efficient preliminary action.
Solution Approach 2:
The patent extracts only the essential key colors from user images that are necessary for gradient generation, rather than processing the entire image data. This extraction approach enables personalization by using image-specific color palettes while reducing processing time and resources by focusing only on the critical color information needed for gradient synthesis.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for providing content to user devices. One of the methods includes receiving user generated content from a user device; identifying an image associated with the user; identifying one or more key colors from the image; generating a gradient based on one of the one or more key colors; and generating content for delivery to user devices using the user generated content, the image, and the generated gradient.