中国科学技术大学学报 ›› 2016, Vol. 46 ›› Issue (1): 47-55.DOI: 10.3969/j.issn.0253-2778.2016.01.007

• 论著 • 上一篇    

基于大规模流式车牌识别数据的即时伴随车辆发现

朱美玲,王雄斌,张守利,刘晨,韩燕波   

  1. 1.天津大学计算机科学与技术学院,天津300072; 2. 北方工业大学大规模流数据集成与分析技术北京市重点实验室,北京100144; 3. 北方工业大学云计算研究中心,北京100144
  • 收稿日期:2015-08-27 修回日期:2015-09-29 接受日期:2015-09-29 出版日期:2015-09-29 发布日期:2015-09-29
  • 通讯作者: 韩燕波
  • 作者简介:朱美玲,女,1987年生,博士生.研究方向:服务计算,大规模流数据关联分析.E-mail: meilingzhu2006@126.com
  • 基金资助:
    北京市自然科学基金重点项目(4131001),北京市属高等学校创新团队建设与教师职业发展计划(IDHT20130502),北方工业大学“人才强校计划”青年拔尖人才培育计划资助.

Instant traveling companion discovery based on large scale streaming ANPR data

ZHU Meiling, WANG Xiongbin, ZHANG Shouli,LIU Chen, HAN Yanbo   

  1. 1. School of Computer Science and Technology, Tianjin University, Tianjin 300072, China; 2. Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data, North China University of Technology, Beijing 100144, China; 3.Cloud Computing Research Center, North China University of Technology, Beijing 100144, China
  • Received:2015-08-27 Revised:2015-09-29 Accepted:2015-09-29 Online:2015-09-29 Published:2015-09-29

摘要: 提出了一种基于流式大规模车牌识别数据集的伴随车辆(伴随车辆是指在一段持续的时间内一起移动的车辆组群)即时发现方法,可实现即时发现疑似伴随车辆并将其按伴随概率排序.该方法充分利用了云基础设施的并行计算能力,基于整数划分思想建立并行发现的负载均衡模型,优化了伴随车辆的发现性能,可用于对时间敏感的交通应用场景,如发现并监控运钞车等特殊车辆的跟踪车辆等.实验证明,该方法能够有效处理大规模的流式车牌识别数据,并实时地输出发现结果.

关键词: 伴随车辆, 车牌识别数据, 流数据, 即时性, 点伴随

Abstract: Traveling companions are object groups that move together in a period of time. To quickly identify traveling companions from a special kind of streaming traffic data, called automatic number plate recognition (ANPR) data, a framework and several algorithms were presented to discover companion vehicles, which can instantly detect suspicious companion vehicles with their probabilities when they pass through monitoring cameras.The framework can be used in many time-sensitive scenarios like taking surveillance on suspect trackers for specific vehicles. Experiments show that the proposed approach can process streaming ANPR data directly and discover companion vehicles in nearly real time.

Key words: traveling companion, ANPR data, stream data, instant, moment companion

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