Semantic Media Ownership Detection via Feature Extraction
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Solution Overview
Problem
The rapid distribution of media objects on the Internet makes it difficult for copyright holders to track and control the usage of their content, as existing technologies struggle to identify ownership and usage rights, especially in decentralized environments like User Generated Content sites and peer-to-peer networks, where content is often distributed without permission.
Innovation Solution
A monitoring system analyzes media objects for semantic properties, such as TV station logos, to estimate ownership rights, allowing for the restriction of access and integration of advertising revenue sharing between content owners and distributors, using visible or invisible signaling images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If digital watermarks are embedded in media content to identify ownership, then content identification capability is improved, but the system complexity and processing requirements increase significantly
Solution Approach 1:
The patent extracts and analyzes only the most significant semantic features from media content (such as dominant colors, shapes, patterns, or recognizable visual elements) rather than processing the entire media file. This feature extraction approach maintains identification accuracy while significantly reducing computational complexity and processing requirements.
Solution Approach 2:
The patent segments the media content analysis into distinct semantic feature categories (color, shape, pattern, texture) and processes each category independently. This segmentation allows the system to identify ownership rights by analyzing specific semantic properties without needing to process the entire complex media file, thereby reducing overall system complexity.
2Measurement precision
If extensive fingerprinting databases are used to track media ownership, then ownership identification accuracy is improved, but the time required for analysis increases
Solution Approach 1:
The patent extracts only the essential semantic features needed for ownership identification (such as dominant colors, geometric shapes, or distinctive patterns) and compares these extracted features against a reduced set of reference data. This approach maintains accurate ownership identification while significantly reducing the time required for analysis compared to comprehensive fingerprinting databases.
Solution Approach 2:
The patent applies partial analysis by focusing on the most discriminative semantic features rather than analyzing all possible features. This selective analysis approach provides sufficient accuracy for ownership identification without the time cost of exhaustive fingerprinting, achieving a balance between accuracy and processing speed.
3Adaptability or versatility
If media content is transformed (resized, rotated, compressed) to evade detection, then distribution flexibility is improved, but detection reliability deteriorates
Solution Approach 1:
The patent employs parameter-invariant semantic feature extraction that can recognize and identify media content characteristics even when transformation parameters (size, orientation, compression level) change. By analyzing semantic properties that remain consistent across transformations, the system maintains detection reliability while allowing flexible distribution of transformed content.
Solution Approach 2:
The patent uses dynamic analysis methods that adapt to different media transformations in real-time. The system can dynamically adjust its feature extraction and recognition processes to accommodate various transformation types, maintaining reliable detection regardless of how the content has been modified during distribution.
Data Source
AI summary
System and method for identification of ownership to media objects through analysis of semantic information in the media objects are disclosed Semantic information is a term that can be used to describe aspects of the content of a media object that are apparent to a human viewing or listening to the content One embodiment of the invention includes extracting semantic information from a specified media object, matching said semantic information of the specified media object against known semantic information of known media objects, and taking action based on the result of the companson.