Image Template Search Using Embedding Vectors for Fast Replacement
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Solution Overview
Problem
Conventional template search systems are inefficient and prone to user error due to reliance on keyword searches and manual browsing, making it difficult to identify and modify digital images for use in templates.
Innovation Solution
A computing device implements a search system that generates an embedding vector for an input digital image using a machine learning model, allowing for semantically similar templates to be identified and visually pleasing output images to be generated in real time by comparing embedding vectors, and optionally excluding templates with multiple or small-scale images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If keyword search and manual browsing are used to find templates, then users can search for templates using text queries, but the search efficiency is low and users are prone to error in identifying suitable templates
Solution Approach 1:
The patent replaces the mechanical keyword-matching search system with an image-based semantic search system using embedding vectors. Instead of manually searching through templates using keywords, users upload an example image and the system automatically finds semantically similar templates by comparing embedding vectors, dramatically improving both efficiency and accuracy.
Solution Approach 2:
The patent introduces embedding vectors as an intermediary representation between images and templates. The embedding space serves as a mediator that translates visual content into a searchable format, enabling the system to understand and match image semantics without requiring manual keyword input or browsing.
2Ease of operation
If users manually edit digital images in templates, then users can customize templates to their needs, but the process is time-consuming and inefficient
Solution Approach 1:
The patent performs preliminary actions by automatically identifying and replacing candidate images in templates before the user needs them. The system pre-processes the template database by generating embedding vectors for all templates and their candidate images, so when a user uploads an image, the matching and replacement can occur instantly without manual editing time.
Solution Approach 2:
The system enables self-service template customization by automatically matching user-uploaded images with suitable templates and performing image replacements without requiring manual user intervention. The automated image-based search and replacement system handles the entire customization process autonomously.
3Adaptability or versatility
If a large database of templates is maintained, then users have more template options, but searching through the large database becomes inefficient
Solution Approach 1:
The patent transforms the template search problem from a two-dimensional keyword-matching space into a multi-dimensional embedding space. By representing images and templates as vectors in a high-dimensional space, the system can efficiently search through large template databases using distance metrics, maintaining template variety while dramatically improving search speed.
Data Source
AI summary
In implementations of image-based searches for templates, a computing device implements a search system to generate an embedding vector that represents an input digital image using a machine learning model. The search system identifies templates that include a candidate digital image to be replaced by the input digital image based on distances between embedding vector representations of the templates and the embedding vector that represents the input digital image. A template of the templates is determined based on a distance between an embedding vector representation of the candidate digital image included in the template and the embedding vector that represents the input digital image. The search system generates an output digital image for display in a user interface that depicts the template with the candidate digital image replaced by the input digital image.