Automated Highlight Extraction from Sporting Event Video
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Solution Overview
Problem
Creating highlight videos of sporting events manually is time-consuming and costly, as it requires designating split start and end points for each video, necessitating an automated method for extracting highlights.
Innovation Solution
A method and apparatus for automatically extracting highlights from sporting event videos by identifying log information, tagging game information, extracting relevant frames based on keywords, and combining them to create highlight videos, utilizing techniques such as scene change detection and deep learning for game information recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual operation is used to create highlight video by designating split start and end points, then the highlight video can be created with precise control, but it takes time and cost to create highlight video from large amount of videos
Solution Approach 1:
The system performs self-service by automatically analyzing video content, detecting scene changes, and extracting highlight segments without requiring manual intervention. The apparatus autonomously processes large volumes of video data by identifying key moments through automated scene change detection and frame selection, thereby resolving the contradiction between precision and efficiency.
Solution Approach 2:
The patent replaces the mechanical manual operation of designating split points with an automated computational system. The apparatus uses scene change detection algorithms and frame analysis to automatically identify highlight segments, substituting human manual work with automated image processing and pattern recognition techniques.
2Productivity
If automated method is used for highlight extraction, then the time and cost are reduced, but the complexity of the system increases
Solution Approach 1:
The system segments the video processing task into distinct functional modules: scene change detection, frame extraction, highlight identification, and video compilation. By dividing the complex automated process into separate manageable components, the system achieves high productivity while controlling complexity through modular architecture.
Solution Approach 2:
The apparatus employs universal scene change detection algorithms and frame analysis techniques that can be applied across different video types and sporting events. This multi-functional approach allows the same core system to handle various video inputs, reducing overall system complexity while maintaining high automation capability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces the time and cost of creating highlight videos by automatically identifying and combining relevant frames, enabling efficient production of highlight videos based on specific keywords or key moments in sporting events.
Implementation Method 1
The scene change may be detected by converting red-green-blue (RGB) into hue-saturation-value (HSV) and using a histogram difference of the HSV
Implementation Method 2
the histogram difference between a previous frame and a current frame for each channel of each of the HSV is determined and the scene change is determined by comparing the determined histogram difference with a predetermined reference
Data Source
AI summary
A method for highlight extraction capable of automatically extracting a highlight from a video including a sporting event is provided. The method for highlight extraction may include: identifying a video including a sporting event, log information that sequentially records events occurring in the sporting event, and a keyword related to the video; tagging the video with game information related to the video; extracting at least one piece of log information corresponding to the keyword and determining at least one frame that corresponds to the log information extracted from the tagged video; and creating a highlight video by combining the at least one determined frame.