Language Augmented Video Editing via AI Analysis
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Solution Overview
Problem
Existing video editing technologies are cumbersome and require expertise, making it difficult for non-professionals to edit videos effectively, especially in creating adaptive content that matches user-defined characteristics.
Innovation Solution
The system utilizes large language models (LLMs) to assist users in video editing by analyzing user input, generating language descriptions for raw video data, and executing editing actions based on free-form language commands, enabling features like idea brainstorming, video data summarization, and adaptive video content creation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional manual video editing methods are used, then editing precision and control are improved, but ease of operation deteriorates and requires significant expertise and effort
Solution Approach 1:
The patent replaces manual mechanical video editing operations with an AI-based system that uses large language models to automatically analyze video content, generate editing plans, and execute editing actions. Users interact through natural language commands instead of manual toolbar operations, substituting complex mechanical editing processes with intelligent automation.
Solution Approach 2:
The system enables self-service video editing by automatically analyzing uploaded videos, generating detailed editing plans, and executing edits without requiring user expertise. The AI system serves itself by processing video content, identifying relevant segments, and applying editing operations autonomously based on user prompts.
2Ease of operation
If language-based editing commands are used, then ease of operation is improved, but precision and control over editing actions deteriorates
Solution Approach 1:
The system implements feedback mechanisms where the AI analyzes the video content, generates editing plans, presents them to the user for review, and allows iterative refinement. This feedback loop ensures that the automated editing actions align with user intentions while maintaining precision through continuous verification and adjustment.
Solution Approach 2:
The patent segments the video content into distinct clips and scenes, allowing the system to process and edit specific segments independently. This segmentation enables precise control over which parts of the video are edited and how, while maintaining ease of operation through automated processing of each segment.
3Productivity
If automated AI-based editing is used, then productivity is improved, but device complexity and system requirements worsen
Solution Approach 1:
The patent introduces an intermediary layer between the user and the complex AI processing system. This intermediary interface simplifies user interaction by accepting high-level natural language commands and translating them into specific editing operations, shielding users from the underlying system complexity while maintaining high productivity.
Data Source
AI summary
Systems and methods for language augmented video editing are disclosed. A method includes presenting a video editing assistant (e.g., via a communicatively coupled display and/or speaker). The method includes, in response to receiving a request from a user to create adaptive video content that satisfies a set of characteristics identified based on the request i) analyzing, using a first machine-learning model, existing video content to identify portions of the existing video content that satisfy the set of characteristics and ii) for each portion of the existing video content that satisfies the set of characteristics, create adaptive video content using a respective portion of the existing video content that satisfies the set of characteristics. The method includes generating, using a second machine-learning model, descriptions of the adaptive video content and presenting the adaptive video content and the descriptions of the adaptive video content.