Automated Short Video Generation via User-Specific Template Matching
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Solution Overview
Problem
The generation of short videos is inefficient and costly due to the need for manual material editing, video synthesizing, and audio-video synchronization in current processes.
Innovation Solution
A method and apparatus for improving short video generation efficiency by performing video analysis to obtain video segments, matching them with user-specific video templates, and splicing them according to template attributes, reducing manual intervention and computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual material editing, video synthesizing, and audio-video synchronizing are performed, then video quality can be controlled, but generation efficiency is low and computational resources are high
Solution Approach 1:
The video is segmented into multiple video segments based on storyboard processing and attribute analysis. Each segment is tagged with attributes such as scene type, duration, and content characteristics. This segmentation enables automated selection and assembly of video segments according to template requirements, replacing manual editing operations.
Solution Approach 2:
Video templates are created by copying and analyzing successful video structures and patterns. These templates serve as blueprints for automated video generation, where the system replicates proven video flows and structures without requiring manual creation, thereby improving efficiency while maintaining quality standards.
2Adaptability or versatility
If manual video synthesizing and background music adding are performed, then video customization is achieved, but processing time and computational cost increase
Solution Approach 1:
Video templates and attribute tag systems are prepared in advance before actual video generation is needed. The template library includes pre-defined structures, transitions, and music tracks that are ready for immediate application. This preliminary preparation eliminates the need for time-consuming manual synthesis during video generation.
Solution Approach 2:
The system adjusts video parameters such as segment selection, template application, and attribute matching dynamically based on user profiles and content requirements. By changing parameters like video duration, segment composition, and music selection rather than creating videos from scratch, the system achieves customization efficiently.
3Manufacturing precision
If manual audio-video synthesizing is performed, then synchronization precision is improved, but labor cost and processing complexity increase
Solution Approach 1:
The system performs self-service synchronization by automatically aligning audio tracks with video segments based on pre-established temporal relationships and attribute matching. The automated system handles synchronization tasks independently without requiring manual intervention, achieving precise alignment through algorithmic processing rather than manual adjustment.
Data Source
AI summary
Embodiments of the disclosure provide a data processing method and apparatus, a device, and a medium. The method includes: performing video analysis on video data of a target video to obtain a plurality of video segments; determining a video template associated with a target user from a video template database based on a user portrait of the target user, and obtaining at least one predetermined template segment and a template tag sequence in the video template; screening at least one video segment matching the template attribute tag of the at least one template segment; splicing the at least one matched video segment according to a position of a template attribute tag of each template segment in the template tag sequence as a video material segment of the target video; and pushing the video data and the video material segment to an application client corresponding to the target user.