...
首页> 外文期刊>IEICE Transactions on Information and Systems >SHOT: Scenario-Type Hypothesis Object Tracking with Indoor Sensor Networks
【24h】

SHOT: Scenario-Type Hypothesis Object Tracking with Indoor Sensor Networks

机译:SHOT:室内传感器网络的场景类型假设对象跟踪

获取原文
获取原文并翻译 | 示例
           

摘要

In the present paper, we propose an object tracking method called scenario-type hypothesis object tracking. In the proposed method, an indoor monitoring region is divided into multiple closed micro-cells using sensor nodes that can detect objects and their moving directions. Sensor information is accumulated in a tracking server through wireless multihop networks, and object tracking is performed at the tracking server. In order to estimate the trajectory of objects from sensor information, we introduce a novel concept of the virtual world, which consists of virtual micro-cells and virtual objects. Virtual objects are generated, transferred, and deleted in virtual micro-cells according to sensor information. In order to handle specific movements of objects in micro-cells, such as slowdown of passing objects in a narrow passageway, we also consider the generation of virtual objects according to interactions among virtual objects. In addition, virtual objects are generated when the tracking server estimates loss of sensor information in order to decrease the number of object tracking failures. Through simulations, we confirm that the ratio of successful tracking is improved by up to 29% by considering interactions among virtual objects. Furthermore, the tracking performance is improved up to 6% by considering loss of sensor information.
机译:在本文中,我们提出了一种称为场景类型假设对象跟踪的对象跟踪方法。在提出的方法中,使用可检测物体及其移动方向的传感器节点将室内监视区域划分为多个封闭的微单元。传感器信息通过无线多跳网络累积在跟踪服务器中,并且在跟踪服务器上执行对象跟踪。为了从传感器信息估计对象的轨迹,我们引入了虚拟世界的新概念,该概念由虚拟微单元和虚拟对象组成。虚拟对象根据传感器信息在虚拟微单元中生成,传输和删除。为了处理微细胞中对象的特定运动,例如在狭窄通道中通过的对象的减速,我们还根据虚拟对象之间的相互作用来考虑虚拟对象的生成。另外,当跟踪服务器估计传感器信息丢失时,会生成虚拟对象,以减少对象跟踪失败的次数。通过仿真,我们确认通过考虑虚拟对象之间的交互,成功跟踪的比率最多可提高29%。此外,考虑到传感器信息的丢失,跟踪性能可提高高达6%。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号