Large-scale license plate analytics for convoy detection

用于车队检测的大规模车牌分析

• 批准号: 486389-2015
• 负责人: Rabbat, Michael
• 金额: $ 1.92万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=600269
• 关键词: Large; scale; license; plate; analytics

This project aims to develop computational methods for analyzing streams of license plate recognition (LPR) data. LPR cameras, positioned along roads or mounted on law-enforcement vehicles, capture and record observations (time and location) of the license plates of vehicles passing by. Based in Montreal, Genetec, Inc., is a leading provider of LPR technologies to the world-wide market, and this project builds on an existing collaboration between the research team at McGill and Genetec. The aim of this project is to study and develop statistical algorithms for detecting groups of vehicles traveling together (convoys) using streams of LPR events recorded by a collection of cameras around a city. The ability to detect and track convoys would be useful to law enforcement offices for, e.g., helping to catch car thieves, or for catching criminals transporting or smuggling illicit goods. One challenging aspect of this task is to develop algorithms that can distinguish between groups of vehicles that are truly traveling together as a convoy and vehicles which just happen to be near each other for an extended period due to traffic patterns (e.g., during rush hour, or along a long stretch of highway). Another challenge is to develop algorithms that are capable of scaling to handle very large LPR systems (hundreds of cameras, with each camera reporting many thousands of events per hour). This project will focus on developing scalable convoy detection methods combining developments in sparse signal processing, matrix factorization, and optimization. We will also consider the task of efficiently implementing a convoy detection system using a cluster of computers in the cloud, and contributions will be made to literature on large-scale and distributed optimization for matrix factorization. The technology developed in this project will be transferred to Genetec and integrated into their AutoVu product, and success of this project is likely to lead to the creation of new jobs. Through Genetec's technology and services, these methods will be available to law enforcement agents in Canada and around the world.

本项目旨在开发分析车牌识别（LPR）数据流的计算方法。定位在道路两旁或安装在执法车辆上的LPR摄像头，捕捉并记录过往车辆车牌的观察结果（时间和位置）。总部位于蒙特利尔的Genetec公司是全球LPR技术的领先供应商，该项目建立在麦吉尔大学和Genetec研究团队之间现有合作的基础上。这个项目的目的是研究和开发统计算法，利用城市周围的一系列摄像头记录的LPR事件流来检测一起行驶的车辆组（车队）。探测和跟踪车队的能力对执法部门来说是有用的，例如，帮助抓捕偷车贼，或抓捕运输或走私非法货物的罪犯。这项任务的一个具有挑战性的方面是开发算法，以区分真正作为车队一起行驶的车辆组和由于交通模式（例如，在高峰时间，或沿着一段很长的高速公路）而碰巧彼此靠近的车辆组。另一个挑战是开发能够扩展到处理超大型LPR系统（数百个摄像机，每个摄像机每小时报告数千个事件）的算法。该项目将重点开发可扩展的车队检测方法，结合稀疏信号处理、矩阵分解和优化的发展。我们还将考虑使用云中的计算机集群有效实现车队检测系统的任务，并将对矩阵分解的大规模和分布式优化的文献做出贡献。通过该项目开发的技术将被转让给Genetec公司，并整合到他们的AutoVu产品中，如果该项目成功，将会创造新的就业机会。通过Genetec的技术和服务，这些方法将提供给加拿大和世界各地的执法人员。