📄 中文摘要
在经历了一段时间的健身训练后，个人对锻炼姿势的困扰促使了一个可重用的多通道处理（MCP）服务器的开发，用于视频智能分析。尽管录制训练视频提供了反馈，但在回放时仍面临困难，尤其是在快速浏览和对比不同动作时。通过将这一视觉模式匹配任务与多模态AI技术结合，旨在提高视频分析的效率和准确性，从而为个人训练提供更好的支持。
教会大型语言模型观看视频：一种通用的帧级 AI 分析模式
📄 English Summary
Teaching an LLM to Watch Video: A General-Purpose Pattern for Frame-Level AI Analysis
A personal frustration with workout form led to the development of a reusable Multi-Channel Processing (MCP) server for video intelligence analysis. Recording workout sessions provided some feedback, but reviewing the footage posed challenges, particularly when trying to compare different repetitions quickly. By integrating this visual pattern-matching task with multimodal AI technology, the goal is to enhance the efficiency and accuracy of video analysis, ultimately offering better support for personal training.