Media Search Navigation Using Captions, Tags, and Recognition
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Solution Overview
Problem
Conventional mechanisms for navigating media content, such as fast forwarding, rewinding, and skip operations, are inefficient and imprecise, and existing search methods fail to provide easy access to specific media segments featuring desired content.
Innovation Solution
Analyzing metadata, closed captions, social media content, and tags, combined with image and audio recognition algorithms, to identify and highlight relevant media segments, allowing precise navigation through media content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If fast forward and rewind operations are used for navigation, then users can move through media content, but navigation becomes highly inefficient and imprecise
Solution Approach 1:
The system performs preliminary analysis of media content during playback, continuously generating captions and metadata in the background. This preliminary action prepares search-ready data structures without interrupting user viewing, so when a search query is entered, the system can immediately retrieve relevant segments without requiring time-consuming manual scanning or processing.
2Measurement precision
If skip forward and skip backward capabilities are used, then navigation through media content is enabled, but precision and efficiency remain insufficient
Solution Approach 1:
The patent replaces manual mechanical navigation (fast forward, rewind, skip operations) with an automated information-based system. Image recognition, audio analysis, and caption generation create a digital map of content that enables direct jumping to specific segments through search queries, substituting inefficient mechanical time-based navigation with precise information-based positioning.
3Adaptability or versatility
If bookmarks are provided for navigation, then access to specific segments is improved, but the system lacks adaptability to user-specific search needs
Solution Approach 1:
The system implements a universal search mechanism that handles multiple types of queries simultaneously - text-based searches using generated captions, image-based searches using frame analysis, and metadata-based searches using extracted information. This single multi-functional search system replaces the need for multiple specialized navigation tools while adapting to diverse user needs through natural language queries.
Data Source
AI summary
Mechanisms are provided to allow for improved media content navigation. Metadata such as closed captioning, social media content, and tags associated with various media segments are analyzed to allow identification of particular entities depicted in the various media segments. Image recognition and audio recognition algorithms can also be performed to further identify entities or validate results from the analysis of metadata.


