Semantic Graph Video Traversal for Non-Linear Playback
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Solution Overview
Problem
Existing video content consumption is limited to linear representation, restricting users' ability to view scenes in orders other than the original publisher's arrangement, which can lead to a less engaging viewing experience and higher user abandonment.
Innovation Solution
A semantic graph is used to associate video content segments with semantic attributes, allowing users to select and view content based on specific attributes, such as characters or plotlines, while maintaining storyline continuity, by reordering playback according to user preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If video content is provided in linear representation as originally arranged by the publisher, then the storyline continuity is maintained, but the user cannot view scenes in custom orders based on personal preferences
Solution Approach 1:
The video content is segmented into individual scenes, each tagged with semantic attributes (characters, locations, objects, events). This segmentation allows the system to reconstruct the video in custom orders while maintaining storyline continuity through dependency tracking. Each scene can be independently selected and reordered based on user preferences.
Solution Approach 2:
The patent introduces a semantic attribute dimension beyond the traditional linear timeline. By organizing scenes along multiple semantic dimensions (characters, locations, events) in addition to temporal sequence, the system enables viewing along different dimensions while preserving the underlying temporal dependencies that ensure storyline continuity.
2Ease of operation
If users are allowed to view scenes in arbitrary orders, then personalized viewing experience is improved, but the complexity of managing scene relationships and dependencies increases
Solution Approach 1:
The semantic graph structure serves multiple functions simultaneously: it organizes scenes by semantic attributes, tracks dependencies between scenes, enables custom ordering, and ensures storyline continuity. This multi-functionality reduces the need for separate complex systems for each function.
Solution Approach 2:
The semantic graph acts as an intermediary layer between the raw video content and the user interface. It abstracts the complex scene relationships and dependencies, presenting a simplified interface to users while managing the underlying complexity of scene ordering and continuity requirements.
3Productivity
If the system provides only linear playback, then the implementation is simple, but user engagement and retention decrease due to lack of personalization
Solution Approach 1:
The playback system transitions from a static linear sequence to a dynamic structure where the playback order can be adjusted based on user selections. The semantic graph enables dynamic reordering of scenes while maintaining the underlying temporal and logical relationships, allowing personalized viewing without requiring a completely new system.
Data Source
AI summary
Disclosed are various examples that relate to providing an alternative viewing experience for video content. A semantic graph corresponding to the content is generated. The semantic graph is traversed and the video content segments corresponding to a selected attribute within the semantic graph are played back in an ordering that can vary from a linear representation of the content.