Content-Adaptive Video Editing With Automatic Material Matching
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Solution Overview
Problem
Existing video editing software requires time-consuming manual selection of video templates for beautification, leading to low matching between effect processing and video content, and limited effect options, making it difficult to achieve personalized and adaptive video processing.
Innovation Solution
A video processing method that extracts video content features, recommends materials matching these features, and generates a target video by adding these materials to the original video, ensuring high matching and personalized processing effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual selection of video templates is used for beautification, then the user can choose from available templates, but the process is time-consuming and reduces processing efficiency
Solution Approach 1:
The system automatically analyzes video content and selects appropriate templates without requiring manual user input. The video processing system performs self-service by autonomously matching video features with suitable templates, thereby eliminating the time-consuming manual selection process while maintaining appropriate template choices
Solution Approach 2:
The system pre-extracts video content features and pre-matches them with appropriate templates in advance. By performing preliminary analysis of video characteristics and pre-selecting suitable templates before the actual processing, the system eliminates the need for manual selection during the editing process, significantly improving processing efficiency
2Extent of automation
If fixed video templates are used for beautification, then the processing can be automated, but the matching between effect processing and video content is poor
Solution Approach 1:
The system applies different templates to different segments of the video based on local content characteristics. By analyzing video features at various time points and applying locally-optimal templates to specific video segments, the system achieves both automation and high adaptability, ensuring each part of the video receives the most appropriate template match
Solution Approach 2:
The system dynamically adjusts template selection based on real-time video content analysis. Rather than applying a fixed template throughout, the system continuously monitors video features and dynamically switches between different templates to match changing content, achieving both automation and high adaptability to video variations
3Extent of automation
If fixed video templates are used, then automation is achieved, but the effect options are limited and personalized processing is difficult
Solution Approach 1:
The system changes multiple parameters including video content features, template characteristics, and matching weights to achieve personalized processing. By adjusting these parameters based on video analysis results and user preferences, the system provides diverse effect options while maintaining full automation, enabling personalized video beautification without limiting effect choices
Data Source
AI summary
Embodiments of the present disclosure relate to a video processing method and apparatus, a device and a medium. The method comprises: extracting a video content feature based on an analysis of an original video; obtaining at least one recommended material that matches the video content feature; and generating a target video by processing the original video according to the at least one recommended material, wherein the target video is a video generated by adding the at least one recommended material to the original video.