用摄像头实现会场进出自动识人，动态识别准确率超90%
Automated Attendee Recognition System for Large-Scale Social Events or Conference Gathering
- 部署门禁摄像头实时传视频至云端，做人脸检测与识别
- 90%识别准确率，每帧处理仅5秒，支持无死角自然走动识别
- 适合大型活动安保，尤其对遮挡少的人员识别率达100%
大型社交活动（如婚礼、会议）中人工点名效率低且易出错。为此，我们提出一种基于云的自动化考勤系统，利用入口/出口处安装的摄像头持续采集视频，并上传至云端进行实时人脸检测与识别。与现有方案不同，本系统可在参与者未直视镜头时仍准确识别，支持自然行走、环顾或交谈等动作。据我们所知，这是首个在动态场景下实现高识别率的系统。系统整体识别准确率达90%，单帧处理时间5秒，确保实时运行且不丢帧；同时在相同延迟内向安保人员发送提醒。对于无面部遮挡者，识别准确率达100%，且能成功识别进入摄像头视野的所有人员，为大规模社交活动提供可靠考勤解决方案。
原文摘要 · Abstract (English)
Manual attendance tracking at large-scale events, such as marriage functions or conferences, is often inefficient and prone to human error. To address this challenge, we propose an automated, cloud-based attendance tracking system that uses cameras mounted at the entrance and exit gates. The mounted cameras continuously capture video and send the video data to cloud services to perform real-time face detection and recognition. Unlike existing solutions, our system accurately identifies attendees even when they are not looking directly at the camera, allowing natural movements, such as looking around or talking while walking. To the best of our knowledge, this is the first system to achieve high recognition rates under such dynamic conditions. Our system demonstrates overall 90% accuracy, with each video frame processed in 5 seconds, ensuring real time operation without frame loss. In addition, notifications are sent promptly to security personnel within the same latency. This system achieves 100% accuracy for individuals without facial obstructions and successfully recognizes all attendees appearing within the camera's field of view, providing a robust solution for attendee recognition in large-scale social events.
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