Content Boundary Detection for Video Substitution
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Solution Overview
Problem
Existing systems for electronic broadcast communications fail to effectively detect and substitute content changes, particularly from event programming to interstitial advertising, leading to inappropriate advertising being displayed to viewers.
Innovation Solution
A two-stage process for detecting content boundaries using a digital processor, which identifies changes in video frames and compares them to a database of representative interstitial video segments to automatically switch to alternate content, such as more relevant advertising or prerecorded content, and returns to the original content when appropriate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If automated content detection and substitution system is implemented, then content relevance and user experience are improved, but device complexity and processing requirements increase
Solution Approach 1:
The content detection process is divided into two distinct stages: first identifying candidate frames through change detection algorithms, then verifying them through database comparison. This segmentation allows the system to manage complexity by breaking down the overall task into manageable, modular components that can be processed sequentially.
Solution Approach 2:
A database of representative interstitial video segments is prepared in advance before runtime operation. This preliminary action enables the system to quickly verify detected content boundaries by comparing against pre-stored patterns, reducing real-time processing complexity while maintaining high detection accuracy.
2Adaptability or versatility
If content substitution is performed during interstitial periods, then user experience is improved, but loss of original broadcast content timing occurs
Solution Approach 1:
The system dynamically adjusts content delivery based on real-time detection of content boundaries, switching between original broadcast content and substitute content as needed. This dynamic approach allows the system to maintain appropriate content relevance while adapting to the timing constraints of live broadcast schedules.
Solution Approach 2:
The content detection and substitution system acts as an intermediary layer between the broadcast signal and the user display, enabling content replacement during interstitial periods while preserving the overall broadcast timing structure. The system manages the transition between original and substitute content without disrupting the broadcast schedule.
3Measurement precision
If detailed video frame analysis is performed for content boundary detection, then detection precision is improved, but processing time and computational load increase
Solution Approach 1:
The detection process is segmented into two phases: rapid identification of candidate frames using change detection, followed by precise verification through database comparison. This segmentation enables the system to achieve high detection precision while minimizing overall processing time by only performing detailed analysis on promising candidates.
Solution Approach 2:
The system performs partial analysis on all frames (change detection) and excessive/detailed analysis only on candidate frames (database comparison). This selective application of analysis depth optimizes the balance between detection precision and processing time by avoiding full detailed analysis of every frame.
Data Source
AI summary
A method of automated content selection is disclosed, in which an end user views multimedia content provided via by a content aggregator that is also programmed to detect content delivery boundaries. This occurs, for instance, when the provider switches from showing an event to showing interstitial advertising. On detecting a delivery boundary, a substitute stream of multimedia content is then automatically sent. Detecting a content delivery boundary is accomplished in a twostep process. First, a candidate frame indicative of a deliver boundary is found. This is done, for instance, by finding a change in average sound volume of sufficient magnitude. The candidate frame is then compared to a database of representative frames of known interstitial video segments. If a sufficiently good match is found, the frame is determined to be a content boundary frame, and appropriate switching of the video being relayed is made.