Relevance-Normalized Video Timeline Navigation
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Solution Overview
Problem
Conventional video-sharing services provide limited video navigating capabilities, making it difficult for users to find relevant videos as thumbnails often correspond to regular intervals rather than the most relevant content, and may not depict the intended content even if the full video does.
Innovation Solution
The system allows users to navigate video clips by scrolling through thumbnails normalized by relevance, dynamically selecting thumbnails based on user interactions and timeframe, using machine learning to identify points of interest and arrange them chronologically in a visual menu.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If thumbnails are displayed at regular intervals in a timeline, then the navigation structure is simple and easy to implement, but the thumbnails may not depict the most relevant content even if the full video contains it
Solution Approach 1:
The patent changes the parameter of thumbnail selection from fixed regular intervals to dynamic relevance-based selection. The system analyzes video content and metadata to determine relevance scores, then selects thumbnails that maximize relevance to user queries while maintaining chronological ordering. This transforms the navigation from a static grid to an adaptive, content-aware system.
Solution Approach 2:
The patent introduces an intermediary relevance analysis layer between the video database and the thumbnail display. This intermediary component processes video metadata, content analysis, and user query information to generate relevance scores, which then guide thumbnail selection. This mediator enables the system to balance chronological organization with relevance optimization.
2Productivity
If all videos in a large collection are made accessible through traditional navigation, then complete access is provided, but processing and bandwidth costs increase significantly
Solution Approach 1:
The patent extracts and prioritizes only the most relevant videos and their key thumbnail frames for display, rather than loading or processing entire video collections. The system retrieves metadata and selected thumbnail images for relevant videos while leaving full video data unloaded until explicitly requested. This extraction approach dramatically reduces initial processing and bandwidth requirements.
Solution Approach 2:
The patent applies partial action by loading and processing only a subset of videos deemed most relevant to the user query, rather than processing the entire video collection. The relevance-based filtering enables the system to perform sufficient action on critical videos while avoiding unnecessary processing of less relevant content, optimizing the balance between completeness and efficiency.
3Measurement precision
If thumbnails are selected based on relevance to user input, then the most relevant videos are highlighted, but the system complexity increases due to relevance calculation requirements
Solution Approach 1:
The patent performs preliminary action by pre-calculating and storing video metadata, content tags, and relevance indicators during video ingestion and processing. This advance preparation creates an indexed knowledge base that enables rapid relevance assessment during user queries without requiring complex real-time analysis. The preliminary structuring of data simplifies the query-time relevance calculation.
Solution Approach 2:
The patent segments the relevance calculation into multiple independent components: metadata matching, content tag analysis, user profile correlation, and query keyword weighting. Each segment can be processed separately and combined through weighted aggregation. This segmentation reduces the complexity of any single calculation while maintaining overall measurement precision.
Data Source
AI summary
Methods, systems, and storage media for video navigation normalized by relevance are disclosed. Exemplary implementations may: obtain a plurality of videos recorded in a chronological order; stitch the plurality of videos together in a timeline based on the chronological order, the timeline comprising a visual menu; obtain information associated with the plurality of videos; determine, based on a measure of relevance, a ranking of videos among the plurality of videos; determine, based on the ranking of videos, one or more salient videos from among the plurality of videos, the one or more salient videos comprising a video that is within a range of the ranking of videos; obtain one or more representations associated with individual ones of the one or more salient videos; and cause display of the one or more representations in the timeline, the representations being arranged based at least in part on the chronological order.