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Privacy-Preserving Understanding of Human Body Orientation for Smart Meetings

机译：保护智能会议人体定位的隐私理解

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摘要

We present a method for estimating the body orientation of seated people in a smart room by fusing low-resolution range information collected from downward pointed time-of-flight (ToF) sensors with synchronized speaker identification information from microphone recordings. The ToF sensors preserve the privacy of the occupants in that they only return the range to a small set of hit points. We propose a Bayesian estimation algorithm for the quantized body orientations in which the likelihood term is based on the observed ToF data and the prior term is based on the occupants' locations and current speakers. We evaluate our algorithm in real meeting scenarios and show that it is possible to accurately estimate seated human orientation even with very low-resolution systems.
机译：我们介绍了一种通过融合从向下尖头的飞行时间（TOF）传感器收集的低分辨率范围信息来估算智能房间中坐姿的身体取向的方法，该信息来自来自麦克风录像的同步扬声器识别信息。 TOF传感器保持占用者的隐私，因为他们只会将范围返回到一小部分的生命值。我们提出了一种贝叶斯估计算法，用于量化的身体取向，其中似然术语基于观察到的TOF数据，并且先前的术语基于乘员的位置和当前扬声器。我们在真正的会议场景中评估我们的算法，并表明即使使用非常低分辨率的系统，也可以准确估计坐在的人体方向。

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