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An Object Tracking Method based on Scenario-Type Hypothesis Tracking in Segmented Multiple Regions

机译:基于场景类型假设跟踪的分段多区域目标跟踪方法

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In recent years, wireless communication technologies such as ZigBee have been developed. By constructing a wireless sensor network from infrared sensors with those wireless technologies, it is possible to track moving objects in a wide monitoring region. In this paper, we propose an object tracking method by dividing a wide monitoring region into small multiple regions called "micro cells". Pair of infrared sensors is placed at borders among micro cells to detect objects and their movement direction, and sensor information are gathered to a tracking server through wireless or wired networks. In our proposed method, the tracking server maintains virtual micro cells and virtual objects which indicate a variety of hypotheses of object trajectories. A virtual object is generated, moved, and removed in virtual micro cells appropriately according to sensor information and interactions among virtual objects, so that the tracking server keeps a number of object trajectory hypotheses for each object. When an object departs from the monitoring region, the virtual object with highest likelihood is selected as the estimated object trajectory. Through preliminary simulation evaluations, we confirm that tracking accuracy is improved up to 1.94 times higher by making virtual objects appropriately.
机译:近年来,已经开发了诸如ZigBee的无线通信技术。通过使用这些无线技术从红外传感器构建无线传感器网络,可以在广阔的监视区域中跟踪移动物体。在本文中,我们提出了一种将宽范围的监视区域划分为多个小的区域(称为“微单元”)的对象跟踪方法。一对红外传感器放置在微单元之间的边界以检测对象及其移动方向,并且传感器信息通过无线或有线网络收集到跟踪服务器。在我们提出的方法中,跟踪服务器维护虚拟微单元和虚拟对象,这些虚拟微单元和虚拟对象指示对象轨迹的各种假设。根据传感器信息和虚拟对象之间的交互,在虚拟微单元中适当地生成,移动和删除虚拟对象,以便跟踪服务器为每个对象保留许多对象轨迹假设。当对象离开监视区域时,选择可能性最高的虚拟对象作为估计对象轨迹。通过初步的仿真评估,我们确认通过适当制作虚拟对象,跟踪精度可提高高达1.94倍。

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