Text-to-Image Query Generation for Search Accuracy
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Solution Overview
Problem
Users face challenges in using image-based search algorithms without an existing image query, as they may lack the necessary skills or tools to create a specific image for querying.
Innovation Solution
The system generates a queryable image from text input using a generative machine learning model, allowing users to create a doodle or provide text descriptions that are then transformed into images for use in image-based search algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users use text-based search to find images, then the search process is simple and accessible, but the accuracy and effectiveness of results deteriorate compared to image-based search
Solution Approach 1:
The patent introduces an intermediary system that converts text queries into image queries. The text-to-image generation model acts as a mediator between the user's text input and the image search algorithm, transforming the query format while maintaining the ease of text-based interaction. This resolves the contradiction by enabling image-based search accuracy through text input convenience.
Solution Approach 2:
The system changes the parameter form of the query from text representation to visual representation. By transforming the query parameters from linguistic descriptors to visual features through generative modeling, the system maintains text-based input simplicity while achieving image-based search precision.
2Measurement precision
If users create custom image queries to improve search accuracy, then search effectiveness improves, but the complexity of the process and required skills increase
Solution Approach 1:
The system enables self-service by automatically generating the query image from the user's text description without requiring manual image creation. The generative model performs the complex image synthesis task autonomously based on simple text input, eliminating the need for users to possess image creation skills or tools.
Solution Approach 2:
The system performs preliminary action by pre-generating the query image before the actual search process. This preliminary image generation step prepares the optimal query representation in advance, simplifying the subsequent search operation and eliminating the need for users to manually create images.
3Measurement precision
If users manually create image queries, then search accuracy improves, but the time required for the process increases
Solution Approach 1:
The system establishes continuity of useful action by seamlessly transitioning from text input to image generation to search execution without manual intervention stages. The automated pipeline maintains continuous processing flow, eliminating the time-consuming manual image creation and editing steps while preserving search accuracy.
Solution Approach 2:
The patent replaces the manual mechanical process of image creation with an automated computational system. The generative model substitutes human manual image manipulation with algorithmic image synthesis, dramatically reducing the time required while maintaining or improving search accuracy.
Data Source
AI summary
In some implementations, the techniques described herein relate to a method including (i) receiving, by a processor, user input describing at least one parameter for a query image, (ii) generating, via a generative machine learning model executed by the processor, the query image based at least in part on the user input describing the at least one parameter for the query image, (iii) providing, by the processor, the query image as input to an image-based search algorithm, and (iv) returning a result received by the processor from the image-based search algorithm.