Cooperative Fall Detection with Multiple Cameras

Jian-Chiuan Hou, Weimin Xu, Yuanyuan Chu, Chih-Lin Hu, Ying-Hong Chen, Shi Chen, Lin Hui
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引用次数: 2

Abstract

We propose a fall detection mechanism based on multi-camera cooperation in home space. Cameras capture image-based falling events, and self-organize a group using deep reinforcement learning. Neighbor cameras exchange sensing data and statuses in local network proximity. With information sharing in a group, cameras can improve the accuracy of decision making on falling events and cope with the limited fields of view against physical deployment of cameras in residential areas.
多摄像头协同跌倒检测
提出了一种基于家庭空间多摄像头协同的跌倒检测机制。相机捕捉基于图像的坠落事件,并使用深度强化学习自组织一个群体。相邻摄像机在本地网络邻近中交换传感数据和状态。通过一组信息共享,摄像头可以提高对坠落事件决策的准确性,并应对在居民区部署摄像头的有限视野。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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