基于交通监控流数据的即时旅伴发现

IEEE WISA Pub Date : 2016-09-01 DOI:10.1109/WISA.2016.27
Xiongbin Wang, Chen Liu, Meiling Zhu
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引用次数: 6

摘要

旅伴是在一段时间内一起移动的对象组。为了从一种特殊的流交通数据——自动车牌识别(ANPR)数据中快速识别出伴行车辆,本文提出了一个框架和几种算法来发现伴行车辆。与相关方法相比,我们的主要贡献在于,该框架可以在通过监控摄像头时立即检测到可疑的同伴车辆及其概率。我们的框架可以用于许多时间敏感的场景,比如对特定车辆的可疑跟踪器进行监视。实验表明,该方法可以直接处理流ANPR数据,并能近乎实时地发现伴行车辆。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Instant Traveling Companion Discovery Based on Traffic-Monitoring Streaming Data
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, this paper proposes a framework and several algorithms to discover companion vehicles. Compared to related approaches, our main contribution is that the framework can instantly detect suspicious companion vehicles with their probabilities when they pass through monitoring cameras. Our framework can be used in many time-sensitive scenarios like taking surveillance on the suspect trackers for specific vehicles. Experiments show that our approach can process streaming ANPR data directly and discover the companion vehicles in nearly real time.
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