Automated Video Clip Selection Using Weighted Information Stream Analysis
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Solution Overview
Problem
Current methods for selecting video clips for targeted communications are cumbersome and time-consuming, requiring multiple steps to identify and edit key moments from large video footage, making it difficult to efficiently create effective targeted communications.
Innovation Solution
A system that receives video footage and associated information streams, synchronizes and weights them to identify peaks, selects clips based on these peaks, and optimizes weights using performance metrics to refine the selection process, reducing the effort required to create targeted communications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual methods are used to select video clips for targeted communications, then the selection process allows for human judgment and customization, but the process becomes cumbersome and time-consuming
Solution Approach 1:
The patent replaces manual human judgment and mechanical editing processes with an automated computer-based system that uses machine learning models and algorithms to analyze video footage, identify key moments, and select clips. This substitution of mechanical human operations with automated computational processes directly resolves the contradiction by making the system both easy to operate (automated) and time-efficient (rapid processing).
Solution Approach 2:
The system enables self-service by allowing the automated clip selection process to operate independently without requiring manual intervention. The computer system automatically receives video footage, processes it through multiple information streams, identifies peaks and key moments, and generates selected clips without human assistance, thereby eliminating the time-consuming nature of manual selection while maintaining ease of use through automated operation.
2Productivity
If automated systems are used to identify video clips, then the process becomes faster and more efficient, but the system complexity increases
Solution Approach 1:
The patent segments the complex automated clip selection process into multiple distinct information streams (e.g., audio analysis, visual analysis, metadata processing, engagement metrics) that are processed separately and then integrated. This segmentation allows each component to be optimized independently for efficiency while the modular structure manages overall system complexity by breaking down the monolithic process into manageable, specialized modules.
Solution Approach 2:
The system employs multi-functional computer-based components that can handle multiple types of information processing tasks. For example, the same computational infrastructure processes various information streams (audio, visual, metadata) and performs multiple functions (analysis, identification, selection, optimization), thereby achieving high productivity through versatile automated processing while managing complexity through unified, multi-purpose system architecture.
3Measurement precision
If multiple information streams are analyzed to select video clips, then the quality and relevance of selected clips improve, but the processing complexity and computational requirements increase
Solution Approach 1:
The patent merges multiple information streams (audio, visual, metadata, engagement metrics) into a unified analysis framework where they are processed together to identify key moments. This merging approach improves measurement precision by considering multiple dimensions of video content simultaneously, while managing processing complexity through integrated processing that avoids the overhead of separate independent analyses and enables synergistic optimization across all streams.
Data Source
AI summary
A method for identifying video clips for inclusion in a targeted communication is disclosed. In one embodiment, such a method includes receiving video footage comprising multiple clips. The method receives multiple information streams that are associated with the video footage and synchronizes the information streams with the video footage. The method applies weights to the information streams, aggregates the weighted information streams, and identifies peaks therein. Clips are then selected from the video footage that correspond to the peaks for inclusion in a targeted communication. The method analyzes metrics from the targeted communication to provide feedback in order to optimize the weights. In certain embodiments, optimizing the weights leads to selecting different clips for inclusion in the targeted communication. A corresponding system and computer program product are also disclosed.