Set-Top Box Replay Detection for Automatic Video Highlight Summaries
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Solution Overview
Problem
Viewers lack immediate access to summaries of television programs beyond news broadcasts, as existing summaries are labor-intensive, time-constrained, and only available for general interest events, failing to provide convenient access to content before or after the highlighted event.
Innovation Solution
A set-top box or television receiver device with a processor that automatically identifies and compiles replayed portions of a broadcast by computing metrics for video frames, correlating them to identify repeated content, and creating a summary for immediate viewer access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual compilation of video highlights by producers or reporters is used, then the quality and relevance of highlight summaries can be ensured, but the process becomes labor-intensive and time-consuming
Solution Approach 1:
The system performs automatic highlight identification and compilation without human intervention. The processor autonomously analyzes video content, detects replay segments through frame comparison, extracts key moments, and generates highlight summaries independently, eliminating the need for manual producer involvement while maintaining efficiency
Solution Approach 2:
The patent replaces the manual mechanical process of human viewing and selection with an automated computational system. The processor uses algorithmic frame comparison and metric computation to identify replays, substituting human cognitive labor with mechanical computation that operates faster and without fatigue
2Adaptability or versatility
If news-type summaries are created manually, then highlights can be identified for general interest events, but summaries are only available after time has elapsed and are limited in scope
Solution Approach 1:
The system performs highlight identification and compilation in real-time during the broadcast itself, rather than after the event concludes. By continuously analyzing incoming video streams and detecting replays as they occur, the system prepares summaries immediately available to viewers without post-event processing delays
Solution Approach 2:
The automatic analysis system applies the same replay-detection algorithm to any video content type without requiring human judgment about newsworthiness. This universal approach enables highlight generation for diverse programs including local sports, niche events, and individual games, expanding coverage beyond what manual news teams can handle
3Productivity
If automated replay detection is implemented, then immediate summary creation is possible, but the system requires sophisticated video analysis capabilities
Solution Approach 1:
The video analysis process is divided into discrete manageable steps: frame extraction at regular intervals, metric computation for each frame, sequential comparison of frames to detect repetitions, and final highlight compilation. This segmentation allows complex analysis to be performed through simple, repeatable operations that reduce overall system complexity
Solution Approach 2:
The system transforms visual video content into numerical metrics that represent frame characteristics. By converting image data into comparable numerical values, the system enables automated detection using mathematical operations rather than complex image recognition, simplifying the processing requirements while maintaining accuracy
4Ease of operation
If highlight summaries are manually compiled, then content can be curated for specific time slots, but the summaries are constrained in time and content availability
Solution Approach 1:
The system automatically generates complete highlight summaries without human curation constraints. By autonomously detecting all replay segments in the broadcast and compiling them into comprehensive summaries, the system provides viewers with access to all highlighted content without editorial limitations on quantity or selection
Solution Approach 2:
The system creates complete copies of identified replay segments and assembles them into full highlight summaries. Rather than selecting only certain highlights for broadcast, the system preserves and makes available all detected replay content, allowing viewers to access the complete set of highlighted moments
Data Source
AI summary
Summaries of video programs can be automatically created by identifying and compiling repeated portions of the program content. In many programs (such as broadcasts of sporting events), the most interesting portions of the event are often repeated more than once during the course of the program. By automatically identifying the replayed portions of the video presentation, then, a highlight summary of a television broadcast can be automatically created. Repeated imagery can be automatically identified by comparing metric values representing the contents of video frames. This technique can be implemented within a set top box or other television receiver that is operated by a viewer, thereby providing a high level of flexibility and convenience.