Dynamic Visual Media Extraction for Uninterrupted Playback
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Solution Overview
Problem
Existing systems struggle with extracting and analyzing content from visual media content without interrupting the underlying content, particularly in non-interruptible formats like over-the-air broadcasts, requiring iterative and imprecise search processes.
Innovation Solution
A dynamic content extraction system that identifies a segment of visual media content based on user input, extracts a content data object, and generates a relevance data object using machine learning, all while the content continues uninterrupted, allowing real-time access to contextual information about the content object.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If content extraction is performed without interruption to visual media content, then user viewing experience is maintained and content accessibility is improved, but extraction precision and accuracy deteriorate due to the need for rapid processing
Solution Approach 1:
The system performs preliminary actions by extracting and analyzing content data objects in advance during the visual media content playback, so that when a user requests information about a content object, the relevant data is already processed and ready for immediate delivery, eliminating the need to interrupt playback for extraction
Solution Approach 2:
The system introduces an intermediary processing layer that operates parallel to the visual media content delivery, where content data objects are extracted, analyzed, and indexed in a background processing stream, allowing user queries to be answered from pre-processed data without affecting the main content playback
2Reliability
If iterative search processes are used to locate content information, then extraction completeness is improved, but time consumption increases and user experience deteriorates
Solution Approach 1:
The system performs comprehensive content extraction and analysis in advance during the visual media content playback, building an indexed database of content data objects with their metadata, so that when users search for information, the data is already organized and ready for immediate retrieval without iterative searching
Solution Approach 2:
The system implements feedback mechanisms where extracted content data objects are continuously refined and indexed based on their relevance and importance, allowing the system to optimize future extraction and search operations, reducing time consumption while maintaining completeness
3Loss of information
If computational resources are allocated to content extraction and analysis, then information availability is improved, but system complexity and processing overhead increase
Solution Approach 1:
The system extracts only the essential content data objects and their critical metadata from the visual media content, separating the valuable information from the redundant processing requirements, and stores them in an optimized index structure that minimizes future processing overhead while maintaining information availability
Solution Approach 2:
The system applies different processing intensities to different content data objects based on their importance and user interest, focusing computational resources on extracting and analyzing only the most relevant content elements rather than uniformly processing all content, thereby reducing overall processing overhead
Data Source
AI summary
Various embodiments are directed to apparatuses, methods, computer readable media, computer program products, and systems related to dynamic content extraction in visual media content. In some embodiments the system for dynamic content extraction in visual media content may comprise one or more processors and at least one non-transitory memory comprising instructions that, with the one or more processors, cause the system to receive a segment selection indication associated with visual media content; identify a segment of the visual media content based on temporal indicator associated with the segment selection indication; extract a content data object from at least one portion of the segment of the visual media content; generate a relevance data object based on the content data object; and cause display of the relevance data object to a user.