SoFIT: Self-Orienting Camera Network for Floor Mapping and Indoor Tracking
SoFIT: Self-Orienting Camera Network for Floor Mapping and Indoor Tracking
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DOI：
10.1109/dcoss54816.2022.00029
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发表时间：
2022-05
期刊：
影响因子：
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通讯作者：
Yanchen Liu;Jingping Nie;S. Xia;Jiajing Sun;Peter Wei;Xiaofan Jiang
中科院分区：
文献类型：
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作者：
Yanchen Liu;Jingping Nie;S. Xia;Jiajing Sun;Peter Wei;Xiaofan Jiang
我们提出了SoFIT，一个易于部署和隐私保护的摄像头网络系统，用于乘员跟踪。与传统的基于网络的相机系统不同，SoFIT不需要人来校准网络或提供真实世界的参考。这使得任何人，包括非专业人士，都可以安装SoFIT。安装后，SoFIT会自动定位网络内的摄像头，并利用日常生活中使用空间的人员移动生成楼层地图，然后使用楼层地图和摄像头位置跟踪整个环境中的居住者。我们通过一系列部署证明，SoFIT可以定位摄像头，误差小于4.8cm，生成与实际楼层地图相似度为85%的楼层地图，并以小于7.8cm的误差跟踪居住者。
We present SoFIT, an easily-deployed and privacy-preserving camera network system for occupant tracking. Unlike traditional camera network-based systems, SoFIT does not require a person to calibrate the network or provide real-world references. This enables anyone, including non-professionals, to install SoFIT. Once installed, SoFIT automatically localizes cameras within the network and generates the floor map leveraging movements of people using the space in daily life, before using the floor map and camera locations to track occupants throughout the environment. We demonstrate through a series of deployments that SoFIT can localize cameras with less than 4.8cm error, generate floor maps with 85% similarity to actual floor maps, and track occupants with less than 7.8cm error.