Contextual Watermarking for Proprietary Event Media Filtering
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Solution Overview
Problem
Existing methods for identifying unauthorized video and audio streams from proprietary events are inadequate, as they primarily rely on visual and audio cues and do not effectively utilize contextual information such as location, which can be absent or unreliable.
Innovation Solution
The implementation of contextual watermarking systems that receive and compare reference sensor data with embedded sensor data from media streams to identify and filter out streams not generated at the proprietary event, utilizing primary and secondary contextual cues for accurate event association.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing tools are used to identify unauthorized streams, then the identification process is simple, but the accuracy is low because existing tools are optimized to recognize video content as referenced to professionally recorded and produced material
Solution Approach 1:
The patent transitions from traditional video content analysis to a new dimension by embedding and comparing contextual sensor data (location, temperature, humidity, motion) with media streams. This dimensional shift enables accurate identification of unauthorized streams recorded at proprietary events without requiring complex video content matching algorithms.
2Reliability
If visual and audio cues are used for synchronization, then the synchronization process is straightforward, but the reliability is limited because synchronization is often limited to visual and audio cues in the media stream
Solution Approach 1:
The patent merges multiple synchronization approaches by combining visual and audio cues with contextual sensor data comparison. This integration creates a more reliable synchronization system that uses both traditional media cues and embedded contextual information to accurately identify and synchronize media streams from proprietary events.
Data Source
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AI summary
The present disclosure describes systems and methods for generating and utilizing contextual watermarks. In accordance with an embodiment the method includes: receiving reference sensor data characterizing a proprietary event; receiving a plurality of media streams for potential distribution, each media stream including respective embedded contextual sensor data; for each stream, comparing the reference sensor data with the respective embedded contextual sensor data to identify streams generated at the proprietary event; and distributing only those media streams that are not identified as being generated at the proprietary event.