Visual Search System for Product Component Identification
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Solution Overview
Problem
Consumers face difficulties in finding products online or in physical stores, leading to delayed purchases or the need for in-store assistance, as existing systems lack effective tools for product discovery and recommendation.
Innovation Solution
A visual search system that analyzes product images to identify attributes and components, allowing users to query a database for similar or complementary products based on user-defined preferences, using a graphical user interface to present recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If consumers shop online using traditional product listing and search methods, then they can shop conveniently from home, but they cannot effectively find what they are looking for
Solution Approach 1:
The patent replaces traditional text-based search and manual browsing mechanisms with an image-based visual search system. Users can upload or capture images of products they desire, and the system automatically analyzes these images to identify product attributes, components, and characteristics, then searches the database accordingly. This substitution of mechanical search methods with visual recognition technology resolves the contradiction by maintaining online shopping convenience while dramatically improving product discovery effectiveness.
Solution Approach 2:
The patent introduces an image analysis system as an intermediary between the user's visual intent and the product database. The system acts as a mediator that translates visual information from uploaded images into structured product attributes and search queries, bridging the gap between what consumers see and what the database can understand. This intermediary process enables effective product finding while preserving the convenience of online shopping.
2Measurement precision
If detailed product information and multiple attributes are analyzed to improve product matching, then product recommendation accuracy improves, but system complexity increases
Solution Approach 1:
The patent segments the product analysis process into distinct modules: image preprocessing, attribute extraction, component identification, database querying, and result ranking. Each module handles a specific aspect of the analysis independently, allowing the system to process multiple product attributes without becoming unmanageably complex. This segmentation enables high measurement precision through comprehensive attribute analysis while maintaining system complexity at acceptable levels through modular architecture.
3Measurement precision
If comprehensive product attributes and components are extracted from images, then more accurate product identification is achieved, but processing time increases
Solution Approach 1:
The patent implements preliminary action by pre-processing and indexing product attributes and components in the database before actual search queries. Product images in the database are pre-analyzed to extract attributes, components, and characteristics, and this information is stored in an optimized format for rapid retrieval. During actual product identification, the system compares user-uploaded images against these pre-processed database entries, significantly reducing processing time while maintaining comprehensive attribute analysis for high identification accuracy.
Data Source
AI summary
Example embodiments may provide a system, apparatus, computer readable media, and/or method configured for processing input representing data associated with a first product, the first product comprising a plurality of components, processing input representing a particular one of the components, processing input representing an attribute of the particular component or of the first product, querying a product memory based on the particular component and the attribute to identify a second product.