Signature-Based Content Selection for Broadcast Streams
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Solution Overview
Problem
Existing methods for recording and replaying video and audio data from broadcasts face challenges such as unpredicted delays and commercial insertion, requiring additional information from broadcasters, which can be inaccurate and burdensome.
Innovation Solution
A method using a reference stream with lower data rate, containing fingerprints of the main stream content, allows for fine-grained selection and editing of video and audio streams without needing additional information from the broadcaster, enabling seamless reconstruction and intelligent zapping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If timer controlled recording is used to record and replay selected items from broadcasts, then recording automation is achieved, but recording accuracy is poor due to unpredicted delays and extensions of content items
Solution Approach 1:
The system uses feedback by continuously monitoring the broadcast stream for signature matches and adjusting recording timing dynamically. When a signature is detected, the system triggers recording at that moment rather than relying on pre-set timer schedules, thereby adapting to actual broadcast variations and improving recording accuracy.
Solution Approach 2:
The system performs preliminary action by pre-computing and storing signatures of content items before broadcasting. These signatures serve as reference patterns that enable automatic detection and accurate timing of content items during actual recording, eliminating the need for manual timing adjustments.
2Extent of automation
If timer controlled recording is used, then automated recording is achieved, but commercials and repetitions are inadvertently recorded along with selected content
Solution Approach 1:
The system uses feedback by comparing signatures of the incoming broadcast stream against stored reference signatures. This continuous comparison enables the system to identify and exclude commercials and repetitions based on their unique signature patterns, thereby maintaining content purity while preserving automated recording functionality.
Solution Approach 2:
The system applies the extraction principle by removing unwanted elements (commercials and repetitions) from the recorded content. By detecting these elements through signature matching and excluding them from recording, the system extracts only the desired content items, improving content purity.
3Measurement precision
If additional information such as index tables or mark up tags is provided by broadcasters to improve recording accuracy, then content selection precision is improved, but system complexity and broadcaster overhead increase
Solution Approach 1:
The system applies self-service by generating its own timing and selection information through signature matching, eliminating the need for external index tables or mark up tags from broadcasters. The receiver independently determines content boundaries and timing based on detected signatures, thereby reducing system complexity and broadcaster overhead while maintaining high selection precision.
Solution Approach 2:
The signature-based approach serves multiple functions simultaneously: it provides content identification, timing synchronization, commercial detection, and repetition recognition without requiring separate information systems. This multi-functionality reduces overall system complexity compared to using dedicated index tables or mark up tags for each function.
4Extent of automation
If additional information from broadcasters is used for intelligent zapping and mark-up, then automation capability is improved, but reliability decreases due to errors in additional information
Solution Approach 1:
The system uses feedback by continuously verifying content identity through signature matching during zapping and mark-up operations. This real-time verification ensures that automated operations target the correct content items even when broadcast schedules or metadata are inaccurate, thereby maintaining high reliability while preserving automation capability.
Solution Approach 2:
The system performs self-service by independently verifying content identity through signature detection rather than relying on broadcaster-provided metadata. This self-verification mechanism ensures that intelligent zapping and mark-up operations are based on actual content characteristics, improving reliability while maintaining automation capability.
Data Source
AI summary
A main stream contains successive content elements of video and/or audio information that encode video and/or audio information at a first data rate. A computation circuit (144) computes main fingerprints from the successive content elements. A reference stream is received having a second data rate lower than the first data rate. The reference stream defines a sequence of the reference fingerprints. A comparator unit (144) compares the main fingerprints with the reference fingerprints. The main stream is monitored for the presence of inserted content elements between original content elements, where the original content elements have main fingerprints that match successive reference fingerprints and the inserted content elements have main fingerprints that do not match reference fingerprints. Rendering of inserted content elements to be skipped. In an embodiment when more than one content element matches only one is rendered. In another embodiment matching is used to control zapping to or from the main stream. In another embodiment matching is used to control linking of separately received mark-up information such as subtitles to points in the main stream.