Webpage-to-Video Generation Using Visual and Semantic Matching
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Solution Overview
Problem
Existing methods for generating videos from webpage contents are costly, time-consuming, and of uneven quality due to manual or semi-automatic human-computer interaction, which cannot efficiently meet the demand for large-scale conversion.
Innovation Solution
A method and apparatus for automatic video generation that extracts visual and semantic features from webpage elements, determines matching video materials, and generates videos using these features and materials, reducing manual intervention and costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual or semi-automatic methods are used for video generation, then video quality can be controlled, but production cost increases and production cycle lengthens
Solution Approach 1:
The system performs automatic video generation without manual intervention by extracting webpage elements, generating video scripts through NLP, selecting templates, and rendering videos automatically. This self-service approach eliminates the need for human operators while maintaining consistent quality through automated quality control modules.
Solution Approach 2:
The patent replaces manual mechanical operations with automated computational processes. Webpage crawling, NLP-based script generation, template matching, and video rendering are all performed through software systems rather than human manual work, significantly reducing production costs while maintaining quality through algorithmic control.
2Manufacturing precision
If manual or semi-automatic methods are used for video generation, then video quality can be controlled, but production cycle lengthens
Solution Approach 1:
The system implements continuous automated processing where webpage elements are crawled, scripts are generated, templates are selected, and videos are rendered in an uninterrupted automated workflow. This eliminates idle time between manual operations while maintaining quality control through integrated automated quality assessment at each stage.
Solution Approach 2:
Manual operations are replaced with automated computational processes that execute continuously without human intervention. The automated system performs webpage crawling, NLP processing, template matching, and video rendering in rapid succession, dramatically reducing the production cycle while maintaining consistent quality through algorithmic control.
3Productivity
If automatic video generation is implemented, then production cost decreases and productivity increases, but video quality may become uneven
Solution Approach 1:
The system incorporates automated quality control modules that continuously monitor and assess generated videos against quality standards. Feedback loops adjust generation parameters in real-time to maintain consistent quality across批量 produced videos, ensuring uniform output quality while preserving high automated productivity.
Solution Approach 2:
The automated system dynamically adjusts generation parameters such as template selection criteria, script generation settings, and rendering configurations to optimize video quality consistency. By changing these parameters based on content type and quality requirements, the system maintains uniform quality across diverse video outputs while preserving automated efficiency.
Data Source
AI summary
The disclosure relates to a method, apparatus, medium and electronic device for video generation. The method includes: obtaining webpage elements of a target webpage; extracting visual features and semantic features of the webpage elements; determining a video material matching the target webpage based on the webpage elements, the visual features and the semantic features; and generating a target video based on the video material and the webpage elements. In this way, it is possible to achieve rapid and automatic generation of webpage content into videos, thereby greatly reducing operation costs of a user, and saving video production costs. In addition, automatic recall of the video material can be implemented without manually collecting the video material, thereby saving time and effort.