Media Content Data Extraction via Frequency Rank Stacking
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Solution Overview
Problem
Current methods for extracting data encoded in media content, such as audio streams, face challenges in reliably detecting watermarks due to noise and imperceptible changes in audio signals, which affect the accuracy and reliability of audience monitoring systems.
Innovation Solution
The proposed solution involves a method and apparatus that sample media content signals, convert them into frequency domain representations, determine ranks of specific frequencies, combine these ranks to create a set of ranks, and compare them to reference sequences to extract encoded information. This process includes stacking and averaging ranks to improve detection reliability, especially in noisy conditions, by utilizing a decoder with stack and rank functionality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional watermark detection methods are used to extract data from media content, then the detection process is simple, but the detection reliability is low due to noise and imperceptible changes in audio signals
Solution Approach 1:
The patent applies preliminary action by performing stacking of frequency ranks from multiple consecutive audio frames before进行检测. The system accumulates rank data from N consecutive frames and performs averaging, which prepares the data in advance to enhance the signal-to-noise ratio and improve detection reliability before the actual watermark detection occurs.
Solution Approach 2:
The patent merges multiple frequency rank measurements from consecutive audio frames into a single combined set of ranks through stacking and averaging. This combining process integrates information from multiple time instances, thereby improving detection reliability by reducing the impact of noise and imperceptible changes in any single frame.
2Measurement precision
If ranks from single audio frames are used for detection, then the processing speed is fast, but the accuracy is low due to noise interference
Solution Approach 1:
The patent applies partial action by using only the necessary number of consecutive frames (N frames) for stacking, rather than processing all available data. This selective approach balances accuracy improvement with processing time constraints, achieving enhanced detection accuracy through moderate temporal integration without excessive computational overhead.
Solution Approach 2:
The patent changes the parameter of temporal integration by stacking ranks across N consecutive frames and performing averaging. This parameter change transforms single-frame detection into multi-frame detection, improving measurement precision by reducing noise impact while managing processing time through controlled integration.
3Difficulty of detecting and measuring
If conventional data extraction methods are used, then the system complexity is low, but the ability to detect imperceptible changes is insufficient
Solution Approach 1:
The patent introduces an intermediary process between raw audio signal and final detection: the stacking and averaging of frequency ranks. This intermediary step transforms imperceptible changes in individual frames into amplified, detectable patterns in the combined rank data, enabling detection of subtle watermark signals without requiring complex hardware modifications.
Solution Approach 2:
The patent adds a temporal dimension to the detection process by stacking ranks across multiple consecutive frames. This dimensionality change transforms single-point-in-time detection into multi-temporal-point detection, enhancing the ability to detect imperceptible changes through time-based signal accumulation and averaging.
Data Source
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AI summary
Methods and apparatus to extract data encoded in media content are disclosed. An example method includes receiving a media content signal, sampling the media content signal to generate digital samples, determining a frequency domain representation of the digital samples, determining a first rank of a first frequency in the frequency domain representation, determining a second rank of a second frequency in the frequency domain representation, combining the first rank and the second rank with a set of ranks to create a combined set of ranks, comparing the combined set of ranks to a set of reference sequences, determining a data represented by the combined set of ranks based on the comparison, and storing the data in a tangible memory.