Automated Broadcast Highlight Detection Using Audio Video Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The media industry faces a labor-intensive process in creating highlight reels from broadcast content, as editors must manually identify and extract interesting parts from recorded programs, leading to many broadcasts lacking summarized clips or lists of most interesting times.
Innovation Solution
A computer system that analyzes audio and video content in real-time using advanced signal processing and machine learning to automatically detect periods of heightened emotion or attention, generating a data structure with start and stop times of interesting segments, which can be used to create highlight reels automatically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual editing is used to create highlight reels, then editors can identify interesting parts of broadcast content, but the process becomes labor-intensive and time-consuming
Solution Approach 1:
The patent replaces the mechanical manual editing process with an automated computer-based system that uses audio content recognition, video content recognition, and machine learning algorithms to detect periods of heightened audience interest, thereby eliminating manual labor while maintaining or improving detection accuracy
Solution Approach 2:
The system enables the broadcast content to identify its own interesting segments automatically through embedded analysis of audio and video data, eliminating the need for external human editors and allowing the content to self-categorize its highlight moments
2Reliability
If manual editing is used to create highlight reels, then editors can select candidate clips, but the process requires significant time and resources
Solution Approach 1:
The system performs preliminary analysis of the entire broadcast program in advance, automatically identifying and flagging periods of heightened interest before the highlight reel creation process begins, thereby eliminating the time-consuming manual review process while ensuring reliable selection of interesting segments
Solution Approach 2:
The patent substitutes the time-consuming manual editing workflow with automated computer processing that rapidly analyzes audio and video content using content recognition and machine learning, achieving both high reliability in selection and dramatic reduction in processing time
3Productivity
If automated content analysis is implemented, then highlight reels can be created automatically, but the system complexity increases
Solution Approach 1:
The patent divides the complex automated analysis system into distinct functional modules: audio content recognition, video content recognition, machine learning analysis, and highlight detection, allowing each component to be developed and optimized independently while working together to achieve automated highlight reel creation
Solution Approach 2:
The system employs multi-functional analysis capabilities that can process various types of broadcast content (sports, entertainment, news) using the same core technology platform, reducing overall system complexity by avoiding the need for separate specialized systems for different content types
Data Source
AI summary
This relates to using a computer simulation to test another computer program in real time or simulated real time that is sped up. The disclosed method and system synchronizes information input into the simulation so that the program under test operates in an independent way. The method and system operates a protocol to connect one running computer process, a trading computer program, with another running process, a computer program that executes a market simulation in order to optimize the quality and speed of the simulation and testing of the external computer program.