Multimedia Concept Database Indexing via Signature Clustering
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Solution Overview
Problem
Current multimedia data search engines face challenges in effectively managing and searching vast amounts of multimedia data due to the abstract and complex nature of video content, which cannot be adequately represented by existing metadata, leading to inefficiencies in indexing, clustering, and retrieval processes.
Innovation Solution
A system that generates concept databases by processing multimedia data elements through attention processors, signature generators, clustering processors, concept generators, and index generators to create compact signatures and concept structures, enabling efficient indexing and retrieval by associating metadata with reduced clusters and generating indices for mapping multimedia data to concept structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional metadata solutions are used to describe multimedia content, then the system is simple to implement, but the representation accuracy of complex video content deteriorates
Solution Approach 1:
The patent segments multimedia content into discrete visual concepts through automated detection and recognition systems. The system divides complex video content into individual detectable objects, scenes, and visual elements, each tagged with specific metadata attributes. This segmentation enables precise representation of content without requiring manual annotation of entire videos, thus improving accuracy while maintaining system manageability.
Solution Approach 2:
The patent introduces an intermediary automated content recognition system between the raw multimedia content and the metadata database. This intermediary layer automatically detects, classifies, and tags visual elements, serving as a mediator that transforms complex unstructured content into structured, searchable metadata without requiring direct human intervention, thereby improving representation accuracy while controlling system complexity.
2Reliability
If vast amounts of multimedia data are stored and indexed, then search completeness is improved, but computational resources and processing time increase
Solution Approach 1:
The patent applies preliminary action by pre-processing and pre-tagging multimedia content during ingestion with automated detection systems. Visual concepts, objects, and scenes are identified and metadata is generated in advance, before search operations occur. This preliminary indexing allows the system to maintain comprehensive search capabilities while reducing computational burden during actual search operations, as the heavy lifting of content analysis has already been performed.
Solution Approach 2:
The patent extracts essential visual concepts and metadata attributes from multimedia content, separating the critical search-relevant information from the full content data. By extracting and storing only the essential visual concepts, objects, and scene descriptors in the metadata database, the system achieves comprehensive search capability while minimizing the computational resources required for indexing and querying, as only extracted metadata needs to be processed during searches.
3Measurement precision
If detailed metadata is generated for all multimedia elements, then search precision is improved, but the time and resources required for data processing increase
Solution Approach 1:
The patent applies local quality by generating detailed metadata selectively for specific visual concepts and objects within multimedia content rather than uniformly processing all elements. The automated detection system identifies and applies detailed tagging to salient objects, key scenes, and important visual elements, while using lighter metadata schemas for less critical content. This selective approach maintains high search precision for important elements while reducing overall processing time and resource consumption.
Data Source
AI summary
A system and method for generating a concept database based on at least two multimedia data elements (MMDEs). The method includes: generating at least two items from a received MMDE of the at least two MMDEs; determining the items that are of interest for signature generation; generating at least one signature responsive to at least one item of interest of the received MMDE; clustering at least two signatures received from the signature generator responsive of the plurality of MMDEs; reducing the number of signatures in each cluster to a create a signature reduced cluster (SRC) of the cluster; associating metadata with the SRC to a concept structure including at least two SRCs and their associated metadata; and generating at least one index for mapping the received MMDE to at least one concept structure, wherein the concept database includes concept structures and the generated indices for the at least two MMDEs.