Moodboard Augmentation Using Cross-Modal Generative Image Blending
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Solution Overview
Problem
Existing image curation tools for visual content creators, such as PINTEREST® and BEHANCE®, lack interactive and augmentative capabilities to stimulate the creative ideation process, leading to a manual and aimless exploration of design spaces.
Innovation Solution
A system and method for automated moodboard augmentation via cross-modal generative association making, utilizing a neural network to infer representative text or descriptions from selected images, and generate images based on adjustable sliders to blend adjacent images, providing instantaneous and simultaneous intelligent text-based and image-based augmentations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual searching and scrolling through images is used to explore design space, then visual content creators can find inspiration, but the process becomes time-consuming and aimless
Solution Approach 1:
The patent replaces the mechanical manual searching and scrolling process with an automated AI-based image generation system. The system uses neural networks to generate new images based on semantic concepts extracted from existing images, eliminating the need for manual browsing and significantly improving design exploration efficiency while reducing time investment.
Solution Approach 2:
The system enables self-service by automatically analyzing existing images, extracting semantic concepts, and generating new inspirational images without requiring manual user input for each image. The AI autonomously performs the design exploration work, allowing creators to focus on higher-level creative decisions.
2Adaptability or versatility
If existing image curation tools are used, then images can be organized and displayed, but interactive and augmentative capabilities to stimulate creative ideation are lacking
Solution Approach 1:
The patent merges multiple functions into a single integrated system: image analysis, semantic concept extraction, cross-modal association (text-image), and generative image creation. This combination provides both organizational capabilities and creative augmentation in one tool, enhancing adaptability without requiring separate complex systems.
Solution Approach 2:
The system achieves multi-functionality by serving both as an image curation tool and a creative ideation assistant. It can organize existing images while simultaneously generating new inspirational content, making it versatile for different stages of the design process without increasing perceived complexity for the user.
3Adaptability or versatility
If multiple images are blended to expand design space, then design creativity is enhanced, but the processing complexity increases
Solution Approach 1:
The patent replaces complex manual image manipulation processes with automated neural network-based image generation. The AI handles the complexity of blending multiple images, adjusting semantic concepts, and creating coherent new images, thereby expanding design space without exposing the processing complexity to the user.
Data Source
AI summary
A method for automated moodboard augmentation via cross-modal generative association making is described. The method includes specifying, by a user, a region to augment in their digital workspace, including at least one selected image. The method also includes inferring a representative text, label, or description for the at least one selected image. The method further includes creating a basis for concept blending based on the representative text, label, or description inferred for the at least one selected image. The method also includes generating images in response to an adjustable slider, as adjusted by the user, to adjust how much the generated images should resemble directly adjacent images, including the at least one selected image.