Feature-Based Search Using Visual Fingerprint Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data navigation systems in computing systems are complex and do not align with users' intuitive organizational understanding, making it difficult for users to search for items based on their personal preferences, especially in domains like fashion where visual aesthetics play a crucial role.
Innovation Solution
A system that allows users to search for items by selecting and combining features from multiple items using computer vision and machine learning techniques, generating 'fingerprints' to identify and match visually similar attributes, enabling a more intuitive and personalized search experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional database classification systems are used to organize data, then data storage and retrieval become systematic and manageable, but the system complexity increases and does not align with user intuition
Solution Approach 1:
The patent introduces an intermediary layer between the user and the database classification system. This intermediary translates user-intuitive queries into database-compatible search criteria, allowing users to search using their own mental categorizations without needing to understand the underlying database structure. The system acts as a mediator that converts between user perspective and system organization.
Solution Approach 2:
The patent segments the search process into distinct components: user intent extraction, feature identification, and query translation. By breaking down the complex navigation task into manageable segments, the system reduces the cognitive load on users while maintaining systematic data organization in the background.
2Measurement precision
If detailed classification systems are implemented to improve data organization, then data retrieval accuracy improves, but the ease of operation deteriorates due to increased complexity
Solution Approach 1:
The system performs self-service by automatically analyzing user queries, extracting relevant features, and translating them into precise search criteria. This eliminates the need for users to manually navigate complex classification hierarchies while the system independently achieves accurate retrieval results through automated feature matching and query optimization.
3Adaptability or versatility
If traditional text-based queries are used, then the search system remains simple to operate, but the ability to capture visual aesthetics and fine-grained features is lost
Solution Approach 1:
The patent replaces traditional text-based mechanical query systems with a more advanced approach that incorporates visual feature analysis and machine learning. Instead of relying solely on keyword matching, the system uses image processing and feature extraction to capture visual aesthetics, automatically identifying and weighting relevant visual characteristics to enhance search adaptability.
Data Source
AI summary
Various embodiments of systems and methods allow a system to identify subsets of items by mixing and matching identified features in one or more other items. A system can identify features of items in an item database. The system can then calculate “fingerprints” of these features which are vectors describing the characteristics of the features. The system can present a collection of items and a user can select an item of the collection. The user can then select positive features to include in a search and/or negative features to include in the search. The system can then do a search of the database for items that contain features similar to those positive features and do not contain features similar to those negative features. The user can select features through a variety of means.