The key steps to improve the accuracy of highlight segment recognition include:
- Provide adequate viewing data: Import user viewing behavior data (e.g., length of stay, number of interactions, etc.) into the system in Excel format, and AI will combine visual analysis and behavioral data to make a comprehensive judgment.
- Customized highlight evaluation rules: By modifying the scoring logic in the analyze.py script, it is possible to set the weighting of indicators such as lens switching, face expression, movement frequency, etc. for a specific scene.
- Using Hybrid Recognition Mode: Enable both the system's built-in CV analytics and third-party models integrated with the MCP protocol, which can be combined with the use of AliCloud's eye-tracking models, for example, to enhance recognition.
This answer comes from the articleAi-movie-clip: an AI-driven automated video editing toolThe
May not be reproduced without permission:AI productivity tools " How to achieve high accuracy in automatic video highlight clip editing?
English 
简体中文 
日本語 
Deutsch 
Português do Brasil