Privacy-Preserving and Robust Multimodal Monitoring System Using LWIR and mmWave for Abnormal Behavior Recognition in Hospital Wards

Dongkeun Jeon, Jaebong Lim, Taegu Kim, Yong-Jun Cho, Hyuntae Cho, Yunju Baek
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Abstract

In this paper, we propose a multimodal monitoring sensing system of LWIR camera and mmWave radar for detecting abnormal health behaviors in hospital wards. LWIR cameras can recognize posture with high accuracy while preserving privacy with low resolution. However, it cannot be used in an invisible environment, such as closing curtains in a ward environment. To solve this problem, we intend to solve it using mmWave radar that can be sensed through a thin cloth. We design and implement a multimodal system that uses two sensors for privacy and environmental robustness. For proper use of both sensors, we propose a multimodal black-out network called COMBONet, which switches inputs based on confidence, considering background features and circumstances. Our implementation and experiments used people not used for training as the evaluation. It shows that it can be used comprehensively in various environments.
利用长波红外和毫米波识别医院病房异常行为的隐私保护和鲁棒性多模态监控系统
本文提出了一种由长波红外热像仪和毫米波雷达组成的多模态监测传感系统,用于检测医院病房中的异常健康行为。长波红外摄像机可以在低分辨率下高精度识别姿势,同时保护隐私。然而,它不能用于隐形环境,如病房环境中的窗帘。为了解决这个问题,我们打算使用毫米波雷达来解决,这种雷达可以透过薄布进行感应。我们设计并实现了一个多模态系统,该系统使用两个传感器来保护隐私和提高环境鲁棒性。为了正确使用这两个传感器,我们提出了一种名为 COMBONet 的多模态屏蔽网络,该网络根据可信度切换输入,同时考虑背景特征和环境。我们的实施和实验使用了未用于训练的人作为评估对象。结果表明,它可以在各种环境中全面使用。
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