Multimedia Content Indexing via Feature Segmentation
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Solution Overview
Problem
Traditional search engines are inadequate for effectively searching and retrieving multimedia content, as they primarily rely on textual metadata and ignore the primary content of multimedia files, limiting their ability to provide accurate search results.
Innovation Solution
A method that segments multimedia content into segments, identifies features of different media types within each segment, and assigns relevance to keywords based on the media type and prominence of those features, creating a search index that correlates keywords with relevant segments and files, enabling effective search and retrieval of multimedia content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional search engines rely on textual metadata for searching multimedia content, then the search process is simple and fast, but the search accuracy and relevance are poor
Solution Approach 1:
The patent segments multimedia content into multiple segments and identifies features within each segment separately. This segmentation allows the system to analyze primary content at a granular level, improving search accuracy while managing complexity through structured processing of divided content units.
Solution Approach 2:
The patent performs preliminary feature extraction and keyword identification on multimedia content before actual search operations. By pre-processing content to extract features and generate keywords in advance, the system improves search accuracy without compromising runtime performance, as the complex analysis is completed during the indexing phase.
2Measurement precision
If search engines index all multimedia content in full detail, then search relevance is improved, but processing time and computational resources increase
Solution Approach 1:
The patent applies partial action by focusing feature extraction on salient portions of multimedia content rather than processing every detail uniformly. By identifying and extracting features from key segments and applying different processing depths to different content regions, the system achieves high search relevance while reducing overall processing time and computational resource requirements.
Data Source
AI summary
A method, medium, and apparatus are disclosed for indexing multimedia content by a computer. The method comprises segmenting the multimedia content into a plurality of segments. For each segment, the method identifies one or more features present in the segment, wherein the features are of respective media types. The method then identifies, for each identified feature in each segment, one or more respective keywords associated the identified feature. Then, the method determines, for each identified keyword associated with an identified feature in a given segment, a respective relevance of the keyword to the given segment. The respective relevance is dependent on a weight associated with the respective media type of the identified feature.