Video Content Watermarking via Temporal Alignment
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Solution Overview
Problem
The increasing complexity of media content distribution over computer networks, particularly with video data, makes it difficult to efficiently identify and monitor illicit copies and user usage, as existing techniques are not fast enough to process large amounts of information effectively.
Innovation Solution
A system that embeds unique identifiers within media content, using markers that are strategically placed and varied in video streams, allowing for efficient identification of users and detection of illicit copies by leveraging temporal alignment and fingerprinting techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If markers are embedded in media content for user identification and illicit copy detection, then detection capability is improved, but visual degradation and impact on viewer experience worsen
Solution Approach 1:
The marker is placed in a specific local region of the video content (corner or edge area) rather than throughout the entire content. This localized placement allows the marker to be detectable for identification purposes while minimizing its visual impact on the overall viewer experience
Solution Approach 2:
The marker appears periodically at calculated time intervals rather than continuously. This periodic display reduces the cumulative visual degradation while maintaining sufficient presence for detection and identification purposes
2Reliability
If markers are embedded continuously in media content, then detection reliability is improved, but computational requirements worsen
Solution Approach 1:
The marker is displayed at periodic intervals rather than continuously, which reduces the total number of frames that need to be processed and analyzed, thereby lowering computational requirements while maintaining detection reliability through sufficient sampling
Solution Approach 2:
The marker placement timing is pre-calculated based on the video content characteristics and detection requirements. This preliminary planning optimizes the balance between detection reliability and computational efficiency by placing markers at strategically determined moments
3Ease of operation
If marker placement is fixed and predictable, then ease of detection is improved, but security and resistance to masking worsen
Solution Approach 1:
The marker placement is made dynamic by varying its position, appearance, or timing based on content characteristics or other changing parameters. This dynamic approach maintains detectability through systematic variation while preventing easy prediction by potential copiers or maskers
Solution Approach 2:
The marker's parameters (such as position, color, size, or temporal placement) are changed systematically based on content analysis or other factors. This allows the marker to remain detectable through consistent patterns while avoiding fixed predictability that would compromise security
4Measurement precision
If all frames are processed for marker extraction, then detection completeness is improved, but processing speed worsens
Solution Approach 1:
Instead of processing all frames, the system processes only periodic samples of frames where markers are expected to appear. This selective processing maintains detection completeness for the marker while dramatically improving processing speed by reducing the total number of frames analyzed
Solution Approach 2:
The system performs preliminary analysis to identify frames containing markers before full processing. This preliminary action allows the system to focus computational resources only on relevant frames, improving both detection completeness and processing efficiency
Data Source
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AI summary
A method of securing and/or tracing video media-content which comprises a plurality of frames, the method comprising, receiving at least one candidate media-content which has been determined to have a fingerprint substantially the same as a reference fingerprint generated for the video media-content, processing the candidate media-content after comparison with the video media-content used to generate the reference fingerprint to temporally align the candidate media-content to identify which frames contain the unique identifier; and extracting the unique identifier from the identified frames within the or each candidate video media- content to identify the user ID held within the unique identifier.