Synthetic Image Location Search for Better Query Alignment
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Solution Overview
Problem
Users face challenges in searching for content like clothing, art, movies, and music without an example image, leading to unaligned and time-intensive search results, and current image generation systems are non-intuitive and time-consuming.
Innovation Solution
A computing system that generates model-generated images based on user inputs using an image generation model, which are then processed by a search engine to determine location search results, leveraging user preferences and task graphs for personalized recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If freeform text and Boolean strings are provided as search queries, then the search can be performed without example images, but the search results become mixed, unaligned, and time-intensive to refine
Solution Approach 1:
The patent introduces an image generation model as an intermediary between the text search query and the search engine. The model generates synthetic images from the text query, which then serve as the actual search input. This intermediary transforms imprecise text queries into precise visual representations that yield aligned search results.
Solution Approach 2:
The system performs preliminary image generation before executing the search. By generating synthetic images that represent the user's search intent beforehand, the system prepares a precise visual query that will produce better-aligned results when submitted to the search engine.
2Manufacturing precision
If image queries are used to provide more tailored results, then search accuracy improves, but users may not have access to an image of what they are looking for
Solution Approach 1:
Instead of requiring users to find and provide an example image, the system inverts the approach by generating images from text descriptions. Users input what they are looking for in text form, and the system creates the image query automatically, reversing the traditional workflow.
Solution Approach 2:
The system performs the image creation task automatically without requiring user effort. The image generation model self-generates appropriate query images from the text description, eliminating the need for users to manually source or create example images.
3Adaptability or versatility
If current image generation systems are used with prompt input boxes, then images can be generated from text, but the process is non-intuitive and time-consuming
Solution Approach 1:
The patent merges the image generation task with the search execution into a single integrated workflow. Rather than requiring separate steps for prompt engineering and image generation, the system combines these operations to produce search results more efficiently.
Solution Approach 2:
The system skips the manual prompt engineering step that users would normally need to perform in traditional image generation systems. By automatically translating the search query into appropriate image generation parameters, the system rushes through the process without requiring iterative user refinement.
Data Source
AI summary
Systems and methods for searching using machine-learned model-generated outputs can provide a user with a medium for generating synthetic images depicting synthetic environments that can then be matched to a real world example. The systems and methods can include obtaining a search query, which can be utilized to generate a prompt input that can be processed by an image generation model to generate a plurality of model-generated images. A selection can then be received that selects a particular model-generated image to utilize to query a database.