Caption-Based Video Highlight Generation for Faster Editing
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Solution Overview
Problem
Existing video editing systems require users to manually identify and edit highlights in videos, which is time-consuming and challenging, especially when dealing with multiple video content items.
Innovation Solution
A computer-implemented method and system that automatically generates highlight clips from video content by analyzing the video and audio components, using captioning and transcribing systems to identify key frames and speech, and a highlight generation system to determine relevant content segments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually identify and edit highlights in videos, then they can select relevant content, but the process is time-consuming and inefficient
Solution Approach 1:
The system enables automatic highlight clip generation through self-service mechanisms. The highlight generation system automatically analyzes video content, identifies key moments, and creates highlight clips without requiring manual user intervention. The system serves itself by using AI/ML models to autonomously process video data, extract captions, detect highlights based on predefined criteria, and generate final highlight clips that are then displayed to users for selection.
2Measurement precision
If users re-watch videos multiple times to identify interesting portions, then they can find relevant content, but the process becomes complex and challenging
Solution Approach 1:
The system introduces an intermediary AI/ML-based highlight generation system that acts as a mediator between the raw video content and user needs. This intermediary automatically analyzes video content, generates captions, identifies key moments using machine learning models, and produces highlight clips. This intermediary layer eliminates the need for users to manually re-watch and analyze videos multiple times, thereby reducing operational complexity while maintaining or improving identification accuracy.
3Ease of operation
If users manually edit videos to extract identified portions, then they can create highlight content, but the process requires significant user effort and time
Solution Approach 1:
The system replaces manual mechanical video editing operations with automated computational processes. Instead of users manually cutting, copying, and pasting video segments, the system uses AI/ML models to automatically detect highlights, extract relevant portions, and generate highlight clips. This substitution of mechanical manual operations with automated intelligent systems dramatically reduces user effort and time requirements while maintaining ease of operation through simple user interfaces.
Data Source
AI summary
Described herein is a computer implemented method for generating one or more highlight clips from a video content item. The method includes: receiving a request to generate the one or more highlight clips, the request including the video content item; generating a video script of the video content item, the video script comprising captions for one or more frames of the video content item; identifying one or more highlights in the video content item based on the video script; generating the one or more highlight clips based on the identified one or more highlights; and causing display of the one or more highlight clips in a user interface displayed on a user device.