论文标题
你能走多低？使用Omni方向摄像机检测隐私的人检测
How low can you go? Privacy-preserving people detection with an omni-directional camera
论文作者
论文摘要
在这项工作中，我们使用一个天花板上的Omni方向摄像头来检测房间中的人。这可以用作测量会议室占用的传感器，并计算可用的flex-desk工作空间的数量。如果可以将这些设备集成到嵌入式的低功率传感器中，则它将形成在办公环境中自动化房间预订系统的理想扩展。我们在这里针对的主要挑战是确保拍摄的人们的隐私。我们提出的方法将达到极低的图像分辨率，因此不可能认识到人们或阅读潜在的机密文件。因此，我们通过自动生成的地面真理进行了一个单发低分辨率的人检测网络。在本文中，我们证明了这种方法的功能，并探讨了我们在解决方案方面的水平，以确定识别准确性和隐私保护之间的最佳权衡。由于分辨率较低，结果是一个轻量级网络，可能会在嵌入式硬件上部署。这种嵌入式实现可以开发去中心化的智能相机，该相机仅输出所需的元数据（即会议室中的人数）。
In this work, we use a ceiling-mounted omni-directional camera to detect people in a room. This can be used as a sensor to measure the occupancy of meeting rooms and count the amount of flex-desk working spaces available. If these devices can be integrated in an embedded low-power sensor, it would form an ideal extension of automated room reservation systems in office environments. The main challenge we target here is ensuring the privacy of the people filmed. The approach we propose is going to extremely low image resolutions, such that it is impossible to recognise people or read potentially confidential documents. Therefore, we retrained a single-shot low-resolution person detection network with automatically generated ground truth. In this paper, we prove the functionality of this approach and explore how low we can go in resolution, to determine the optimal trade-off between recognition accuracy and privacy preservation. Because of the low resolution, the result is a lightweight network that can potentially be deployed on embedded hardware. Such embedded implementation enables the development of a decentralised smart camera which only outputs the required meta-data (i.e. the number of persons in the meeting room).
