Video Packaging Service Dynamic Content Stream Generation
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Solution Overview
Problem
Traditional content distribution techniques are limited in dynamically determining opportunities for inserting supplemental content, such as advertisements, into video streams, relying on manual insertion points that are not well-suited for dynamic content adaptation.
Innovation Solution
A video packaging and origination service that encodes content into segments, processes these segments to detect significant events, associates context information, and dynamically generates content streams based on subscription criteria and context, allowing for automatic selection and insertion of supplemental content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual insertion points are used for supplemental content, then content delivery is simple to implement, but adaptability to dynamic content and user interests is poor
Solution Approach 1:
The patent implements dynamic content stream generation where the system continuously monitors video segments, detects significant events using machine learning models, and automatically generates personalized content streams in real-time based on user profiles and contextual information, transforming static manual insertion into dynamic adaptive content delivery
Solution Approach 2:
The system employs automated event detection algorithms and machine learning models that independently analyze video content, identify significant events, and determine optimal supplemental content insertion points without human intervention, enabling the system to self-manage content adaptation
2Loss of information
If dynamic event detection and context-aware content generation are implemented, then content relevance to user interests is improved, but processing time and computational resources increase
Solution Approach 1:
The system pre-generates multiple encoded representations of video segments and pre-processes contextual information about significant events before user requests arrive, storing these prepared content elements in accessible formats that can be rapidly assembled into personalized streams without requiring extensive real-time processing
Solution Approach 2:
The patent divides video content into discrete segments and processes them independently through event detection and contextual analysis, allowing parallel processing of multiple segments and enabling the system to handle content generation tasks more efficiently by working on segmented portions simultaneously rather than processing entire videos sequentially
3Extent of automation
If automated content stream generation is used, then manual intervention is reduced, but system complexity and computational requirements increase
Solution Approach 1:
The patent implements a multi-functional content delivery system that combines video encoding, event detection, contextual analysis, user profile matching, and content stream generation within a unified automated platform, where a single system performs multiple functions that would otherwise require separate manual processes
Data Source
AI summary
A video packaging and origination service can process requests for content segments from requesting user devices. The video packaging and origination service can receive multiple inputs from content sources and determine events in the depictions of the inputs. The video packaging and origination service can generate content streams from the detected events.