Attribute-Based Visual Search System for Dynamic Product Retrieval
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Solution Overview
Problem
Contemporary visual search services lack the ability to dynamically adapt or adjust the attributes associated with products in images prior to search execution, and do not allow users to customize attributes for finding products with similar user-specified attributes.
Innovation Solution
A visual search system and method that uses an image input from a user to generate search results for visually similar products and images, allowing users to select and customize attributes associated with objects in the image, and then uses these attributes to perform a targeted visual search.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If visual search services process images to locate similar products, then product retrieval capability is improved, but user ability to customize search attributes is lost
Solution Approach 1:
The system dynamically adapts the visual search process by allowing users to adjust attributes interactively. The search functionality transitions from a static, fixed-attribute model to a dynamic, user-configurable model where attributes can be modified based on user preferences and feedback, resolving the contradiction between maintaining retrieval capability and enabling customization.
Solution Approach 2:
The system performs preliminary image processing and product identification before presenting results to the user. This allows the system to pre-process images and generate initial search results, then enable users to refine and customize attributes in subsequent iterations, maintaining both efficient retrieval and user control.
2Measurement precision
If visual search services locate products similar in structure or function, then search accuracy is improved, but user control over search criteria is reduced
Solution Approach 1:
The system implements feedback mechanisms where user interactions with search results (such as selecting or rejecting products) are used to refine and adjust search attributes. This feedback loop enables the system to maintain high search accuracy while continuously adapting to user preferences and providing greater effective control to the user.
Solution Approach 2:
The system performs preliminary analysis of the input image to identify products and their attributes, then presents these findings to the user for verification and adjustment. This preliminary action maintains search accuracy through automated analysis while preserving user control by allowing manual review and modification of search criteria.
3Productivity
If visual search services assist users in determining where to purchase products, then purchasing guidance is improved, but attribute customization capability is lost
Solution Approach 1:
The system dynamically integrates purchasing guidance with attribute customization, allowing users to adjust search attributes while simultaneously receiving guidance on where to purchase matching products. The purchasing guidance functionality adapts to user-selected attributes in real-time, resolving the contradiction between providing purchase information and enabling attribute control.
Data Source
AI summary
A visual search system includes a computing device, where the computing device includes an image processing engine for generating a feature vector representing a user-selected object in an image. The computing device also includes, an object detection engine for locating one or more objects in the image and for determining a category of a user-selected object from objects in the image, where the object detection engine uses the category to generate a plurality of attributes for the user-selected object. The computing device further includes a product data store for storing a plurality of tables storing one or more attributes associated with a category of the user-selected object. The computing device additionally includes an attribute generation engine for generating a plurality of attribute options and an attribute matching engine for comparing attributes and attribute options of the user-selected object with attributes and attribute options of visually similar products and images.