期刊文献+

顾及外连通性的PIR传感器网络行为轨迹重构方法 被引量:2

Behavioral Trajectory Reconstruction Method for PIR Sensor Networks Taking into Account Extranet Connectivity
在线阅读 下载PDF
导出
摘要 热释电红外(Passive Infrared,PIR)传感器人体行为研究目前主要集中于特征建模与识别,对轨迹重构的研究相对较少且易忽略传感器布设环境的影响,导致重构结果不确定性较大。为提高重构轨迹的完备性,该文将传感器与环境的连通性作为PIR传感器网络轨迹重构中的约束条件,从空间相邻、时间连续、传感器外连通三方面对轨迹重构过程进行优化。以PIR传感器系统模拟场景中对象随机移动为例,对传感器的响应数据进行轨迹重构,得到对象的连续行为轨迹,结果与场景模拟轨迹基本一致,验证了该文方法的有效性。 Passive infrared(PIR)sensors have been widely used in the analysis of human behavior,such as motion analysis,indoor tracking,and intelligent security.Currently,research in this field primarily focuses on feature modeling and recognition,while research on trajectory reconstruction is relatively limited.Existing trajectory reconstruction methods overlook the impact of sensor distribution environments,resulting in high uncertainty in the reconstruction results.In order to improve the completeness of the reconstructed trajectories,this paper considers the connectivity between sensors and the environment as a constraint in PIR sensor network trajectory reconstruction.The optimization of the trajectory reconstruction process is carried out from three aspects:spatial adjacency,temporal continuity and external connectivity of the sensors.Taking the example of random movement of objects in a PIR sensor system simulation scenario,this paper reconstructs the continuous behavioral trajectories of the objects using response data from the sensors.Through a comparison between the reconstructed trajectories and the actual trajectories in the scenario,it is found that the two sets of trajectories are generally consistent,which confirms the effectiveness of the proposed method.
作者 潘炳煌 滕玉浩 钱凌欣 罗文 俞肇元 PAN Binghuang;TENG Yuhao;QIAN Lingxin;LUO Wen;YU Zhaoyuan(Key Laboratory of Virtual Geographic Environment,Nanjing Normal University,Ministry of Education,Nanjing 210023;State Key Laboratory Cultivation Base of Geographical Environment Evolution(Jiangsu Province),Nanjing 210023;Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application,Nanjing 210023,China)
出处 《地理与地理信息科学》 CSCD 北大核心 2023年第5期1-7,共7页 Geography and Geo-Information Science
基金 国家自然科学基金项目(41971404、42130103) 江苏省研究生科研与实践创新计划项目(SJCX22_0533)。
关键词 热释电红外传感器(PIR) 传感器网络 运动模拟 行为轨迹 轨迹重构 passive infrared(PIR)sensors sensor network motion simulation behavior trajectory trajectory reconstruction
作者简介 潘炳煌(1998-),男,硕士研究生,主要从事路网轨迹数据索引相关研究;通信作者:俞肇元,E-mail:yuzhaoyuan@njnu.edu.cn。
  • 相关文献

参考文献11

二级参考文献76

  • 1王凡,周怀北.基于信号衰减的蜂窝移动定位技术[J].计算机工程与应用,2006,42(9):129-131. 被引量:1
  • 2秦锋,杨波,程泽凯.分类器性能评价标准研究[J].计算机技术与发展,2006,16(10):85-88. 被引量:29
  • 3程光,罗予频,王宏宝.联合轮廓法在低分辨率视频下的多目标追踪[J].计算机工程与应用,2007,43(2):64-66. 被引量:2
  • 4常发亮,马丽,乔谊正.视频序列中面向人的多目标跟踪算法[J].控制与决策,2007,22(4):418-422. 被引量:16
  • 5Alper Y, Omar J, Mubarak S. Object Tracking: A Survey [J]. ACM Computer Survey, 2006, 38(4) : 13 - 57.
  • 6Bennett B, Magee D R, Cohn A G, etal. Enhanced Tracking and Recognition ff Moving Objects by Reasoning about Spatio-temporal Continuity [J]. Image and Vision Computing. 2008, 26(1): 67- 81.
  • 7Ingemar J C, Sunita L H. An Efficient Implementation of Reid's Multiple Hypothesis Tracking Algorithm and Its Evaluation for the Purpose of Visual Tracking [J]. IEEE Trans. Pattern Analysis and Machine Intelligence, 1996, 18(2): 138- 150.
  • 8Bardet F, Chateau T, Laprest' e J T. mumination Aware MCMC Particle Filter for Long-term Outdoor Mulfi-object Simultaneous Tracking and Classification [ C ]//Proceeding of 12th IF-dEE International Conference on Compter Vision, 2009:1623- 1630.
  • 9Xing J L, Ai H Z, Lao S H. Multi-object Tracking Through Occlusions by Loe, al Traeklets Filtering and Global Tracklets Association w/th Detection Responses [C]//Proceeding of 2009 IEEE Computer Vision and Pattern Recognition, 2009:1200 - 1207.
  • 10Perera A, Sfinivas C, Hoogs A, et al. Multi-object Tracking Through Simultaneons Long Occlusions and Split-melge Conditions [C]//Proceeding of 2006 IEEE Computer Vision and Pattem Recognition, 2006:666 - 673.

共引文献121

同被引文献19

引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部