Tracking of objects in a multi-sensor fusion system for border surveillance

Luis Patino, Michael Hubner, M. Litzenberger, J. Ferryman
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Abstract

In this work, we present a Fusion and Tracking system developed within the EU project FOLDOUT aimed to facilitate border guards work by fusing separate sensor information and presenting automatic tracking of objects detected in the surveillance area. The focus of FOLDOUT is on through-foliage detection in the inner and outermost regions of the EU. Fusing several sensor signals increases the effectiveness of detection, particularly in forested and other areas hidden by foliage. We use weighted maps (also called Heatmaps) to combine multi-sensor information; tracking is performed on the resulting fused objects; a track is created or updated based on cost calculation of associating fused detections temporally. We compare tracking results from individual sensors and from fused objects from data collected in a simulated border that is representative of actual EU borders in Bulgaria. The results show how tracking is enhanced if performed on fused data rather than from individual sensor information.
边界监视多传感器融合系统中的目标跟踪
在这项工作中,我们提出了一种融合和跟踪系统,该系统是在欧盟FOLDOUT项目中开发的,旨在通过融合单独的传感器信息和对监视区域检测到的物体进行自动跟踪来促进边防人员的工作。FOLDOUT的重点是在欧盟内部和最外部地区进行树叶检测。融合多个传感器信号可以提高探测效率,特别是在森林和其他被树叶隐藏的地区。我们使用加权地图(也称为热图)来组合多传感器信息;对所得到的融合对象进行跟踪;根据暂时关联融合检测的成本计算创建或更新航迹。我们比较了来自单个传感器的跟踪结果和来自在保加利亚实际欧盟边界代表的模拟边界收集的数据的融合对象。结果表明,如果对融合数据进行跟踪,而不是从单个传感器信息进行跟踪,则可以增强跟踪效果。
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