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Coarse head pose estimation of construction equipment operators to formulate dynamic blind spots

机译:施工设备操作员粗略的头姿势估计以建立动态盲点

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Several hundred workers die in construction in the United States every year because equipment operators are unable to see their fellow workers during operation of their vehicle. In this paper we propose a step towards improving this situation by providing an automated method based on range imaging for estimating the coarse head orientation of a construction equipment operator. This research utilizes commercially-available low resolution range cameras to measure the continuously changing field-of-view (FOV) of an equipment operator in outdoor construction. This paper presents a methodology to measure so-called dynamic blind spot maps. The dynamic blind spot map is then projected on a known static equipment blind spot map that already exists to each construction vehicle. A robust computational coarse head pose estimation algorithm and results to three different pieces of construction equipment and multiple operators are presented. The developed method has the potential in automatically determining the spaces around vehicles that are currently not in the field-of-view of the vehicle operator thus providing eventually additional means and technology for improving safety in construction.
机译:在美国,每年有数百名工人死于建筑施工,因为设备操作员在操作车辆时无法看到他们的同工。在本文中,我们提出了一种通过提供一种基于距离成像的自动化方法来改善这种情况的步骤,该方法可用于估算建筑设备操作员的粗略头部方位。这项研究利用商业上可用的低分辨率范围摄像机来测量室外施工中设备操作员的连续变化的视场(FOV)。本文提出了一种测量所谓动态盲点图的方法。然后将动态盲区图投影到每个工程车辆已经存在的已知静态设备盲区图上。提出了一种鲁棒的计算粗头姿势估计算法,并给出了三​​种不同的建筑设备和多个操作员的结果。所开发的方法具有自动确定当前不在车辆操作者视野内的车辆周围空间的潜力,从而最终提供了用于改善施工安全性的附加手段和技术。

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