Contextual Content Identification for Composite Media Licensing
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Solution Overview
Problem
Existing systems for identifying proprietary content in composite media, such as recorded video game footage, often produce false positives due to complex licensing conditions, failing to distinguish between permitted and unpermitted uses.
Innovation Solution
A computer-implemented method that identifies a first media component as proprietary content and uses a context indicator to determine its context within the composite media, utilizing spatial and temporal offsets and databases to verify if the context is permitted.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing systems compare media files to databases of proprietary content to identify unlicensed usage, then proprietary content can be detected, but false positive results occur when complex licensing conditions are involved
Solution Approach 1:
The patent segments the identification process into multiple components: detecting proprietary content, identifying context indicators, and determining licensing status based on context. This segmentation allows the system to handle complex licensing conditions by evaluating multiple factors rather than relying on a single binary detection, thereby reducing false positives while maintaining detection accuracy.
Solution Approach 2:
The patent introduces context indicators as intermediary elements that mediate between proprietary content detection and licensing determination. These context indicators provide additional information about the usage context, enabling the system to distinguish between licensed and unlicensed uses more accurately, thus reducing false positives without compromising the ability to detect proprietary content.
2Reliability
If the system identifies context indicators and determines context to resolve false positives, then reliability improves, but device complexity increases
Solution Approach 1:
The system segments the complex licensing determination task into manageable components: context indicator identification, context determination, and licensing status evaluation. This segmentation reduces device complexity by breaking down the overall complex process into smaller, more manageable subsystems that can be implemented and maintained more easily.
Solution Approach 2:
The patent performs preliminary actions by identifying context indicators and determining context before making the final licensing determination. This preliminary analysis provides a foundation for more accurate licensing decisions, improving reliability while organizing the complexity into a structured, multi-stage process that is easier to manage.
3Measurement precision
If the system performs comprehensive context analysis to reduce false positives, then measurement precision improves, but loss of time increases
Solution Approach 1:
The system performs preliminary identification of context indicators and context determination before the final licensing decision. This preliminary action allows for efficient processing by preparing the necessary contextual information in advance, enabling faster final determinations while maintaining high measurement precision through comprehensive context analysis.
Solution Approach 2:
The patent applies partial action by focusing context analysis on the most relevant context indicators and circumstances rather than analyzing every possible factor in equal detail. This selective approach maintains measurement precision for critical licensing decisions while reducing overall processing time by avoiding unnecessary analysis of less relevant factors.
Data Source
AI summary
A computer-implemented method for identifying proprietary content in composite media comprising a plurality of media components, the method comprising: identifying a first media component of the composite media as proprietary content; identifying a second media component of the composite media as a context indicator; and determining a context for the proprietary content based on the context indicator.