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Measurement and estimation of indoor human behavior of everyday life based on floor sensing with minimal invasion of privacy

机译:基于地板感应和最小程度的隐私入侵的室内人类日常生活行为的测量和估计

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This paper describes a method of measurement and estimation of human behaviors in a room together with the layout of objects on the floor. The information obtained by the method is essential for a service robot working in a human daily life environment. The method uses only one laser range finder (LRF) installed in the room and a strip of mirror attached to a side wall close to a floor. The area of sensing is limited to a plane parallel to and just a few centimeters above the floor, thus covering the whole room with minimal invasion of privacy of a resident while reducing occlusion. Processing both distance and reflectance acquired by the LRF from the surface of the existing objects allows us to exclude immediately distinguishable clusters and to focus on the analysis of remaining clusters. The human behavior models that we propose are effectively used to estimate human behavior based on the limited LRF data. Our experimental results validate the effectiveness of the proposed method.
机译:本文介绍了一种测量和估算房间中人类行为的方法,以及对象在地板上的布局。通过该方法获得的信息对于在人类日常生活环境中工作的服务机器人至关重要。该方法仅使用安装在房间中的一个激光测距仪(LRF),并将一条镜子固定在靠近地板的侧壁上。感应区域仅限于与地面平行且仅在地面上方几厘米的平面,因此覆盖了整个房间,对居民隐私的侵害最小,同时减少了遮挡。通过处理LRF从现有物体表面获得的距离和反射率,我们可以排除可立即区分的聚类,并专注于分析剩余的聚类。我们提出的人类行为模型可以有效地用于基于有限的LRF数据估算人类行为。我们的实验结果验证了该方法的有效性。

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