Image Search Query Model Using Attribute Associations
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Solution Overview
Problem
Current image search technologies are limited in their ability to effectively identify and retrieve images based on attributes and associations, leading to irrelevant results and inefficient querying processes.
Innovation Solution
A computing device is equipped with a trained query model and an expanded annotated image database that processes queries including attributes and associations, enabling precise matching and retrieval of concept images by integrating attribute and association data with image annotation models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image search uses only basic annotations, then the search system is simple, but the search accuracy and relevance are insufficient
Solution Approach 1:
The patent segments the search system into multiple independent modules: a query processing module that handles attribute and association parsing, a database module that stores annotated images with metadata, and a matching module that processes search queries. This segmentation allows the system to achieve high search accuracy through specialized processing while maintaining manageable complexity through modular architecture.
Solution Approach 2:
The patent implements a nested data structure where image annotations contain multiple levels of attributes and associations. Each image entry includes basic annotations, detailed attributes (color, shape, texture), and associations (relationships with other objects), creating a nested information hierarchy that enables precise search without requiring a completely complex system from the ground up.
2Adaptability or versatility
If the search system includes detailed attributes and associations, then the search coverage is expanded, but the processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-processing and indexing all image attributes and associations before actual search queries are received. The database stores pre-organized metadata structures that map images to their attributes and associations, enabling the search system to quickly match queries against pre-indexed data rather than processing everything in real-time.
Solution Approach 2:
The patent creates a simplified search index that copies only the essential attribute and association information needed for matching, rather than storing complete image data. This indexing approach expands search coverage by maintaining comprehensive metadata while reducing processing time by working with condensed search keys rather than full image datasets during query processing.
3Reliability
If the system processes queries with multiple attributes and associations, then the query results are more relevant, but the query processing complexity increases
Solution Approach 1:
The query processing system segments the complex query into distinct components: concept identification, attribute extraction, and association mapping. Each component is handled by dedicated processing functions that independently analyze specific aspects of the query, making the overall complex query processing manageable through systematic decomposition into simpler sub-tasks.
Solution Approach 2:
The patent introduces an intermediary matching layer that translates complex user queries into standardized search operations. This intermediary module acts as a mediator between the user's complex query requirements and the database storage structure, converting multi-attribute and multi-association queries into simplified matching operations that the database can execute efficiently while maintaining high result relevance.
Data Source
AI summary
A system provides image search results based on a query that includes an attribute or an association and a concept identifier. The query is input into a trained query model to define a search syntax for the query. The search syntax is submitted to an expanded annotated image database that includes a concept image of a concept identified by the concept identifier with a plurality of attributes associated with the concept and a plurality of associations associated with the concept. A query result is received based on matching the defined search syntax to one or more of the attributes or one or more of the associations. The query result includes the concept image of the concept associated with the matched one or more of the attributes or one or more of the associations. The concept image included in the received query result is presented in a display.