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一种用于智慧城市中密集型摄像机网络的语义自主视频监控系统。

A semantic autonomous video surveillance system for dense camera networks in Smart Cities.

机构信息

Universidad de Valladolid, Dpto. TSyCeIT, ETSIT, Paseo de Belén 15, Valladolid 47011, Spain.

出版信息

Sensors (Basel). 2012;12(8):10407-29. doi: 10.3390/s120810407. Epub 2012 Aug 2.

DOI:10.3390/s120810407
PMID:23112607
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3472835/
Abstract

This paper presents a proposal of an intelligent video surveillance system able to detect and identify abnormal and alarming situations by analyzing object movement. The system is designed to minimize video processing and transmission, thus allowing a large number of cameras to be deployed on the system, and therefore making it suitable for its usage as an integrated safety and security solution in Smart Cities. Alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies. This means that the system employs a high-level conceptual language easy to understand for human operators, capable of raising enriched alarms with descriptions of what is happening on the image, and to automate reactions to them such as alerting the appropriate emergency services using the Smart City safety network.

摘要

本文提出了一种智能视频监控系统的提案,该系统能够通过分析物体运动来检测和识别异常和报警情况。该系统旨在最小化视频处理和传输,从而允许在系统上部署大量摄像机,因此使其适合用作智能城市的综合安全和安保解决方案。报警检测是基于移动对象及其轨迹的参数进行的,并使用语义推理和本体进行。这意味着系统采用了易于操作人员理解的高级概念语言,能够用图像上发生的事情的描述来发出丰富的警报,并实现对这些警报的自动化反应,例如使用智能城市安全网络向适当的应急服务发出警报。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/7693e1736d3a/sensors-12-10407f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/d72478578f14/sensors-12-10407f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/62f737f942ff/sensors-12-10407f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/8b1b3cae4d26/sensors-12-10407f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/e5dd8122a028/sensors-12-10407f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/a0824cc613aa/sensors-12-10407f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/2a7aef6ecf9a/sensors-12-10407f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/2107f3ad60f2/sensors-12-10407f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/45e7d878164f/sensors-12-10407f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/ad7f2d972c5c/sensors-12-10407f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/7693e1736d3a/sensors-12-10407f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/d72478578f14/sensors-12-10407f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/62f737f942ff/sensors-12-10407f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/8b1b3cae4d26/sensors-12-10407f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/e5dd8122a028/sensors-12-10407f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/a0824cc613aa/sensors-12-10407f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/2a7aef6ecf9a/sensors-12-10407f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/2107f3ad60f2/sensors-12-10407f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/45e7d878164f/sensors-12-10407f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/ad7f2d972c5c/sensors-12-10407f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e4/3472835/7693e1736d3a/sensors-12-10407f10.jpg

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2
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IEEE Trans Pattern Anal Mach Intell. 2009 Mar;31(3):539-55. doi: 10.1109/TPAMI.2008.87.
3
Robust object recognition with cortex-like mechanisms.具有类皮质机制的稳健目标识别
以低成本高效地向智能家居移动防护设备提供视频监控服务。
Sensors (Basel). 2018 Mar 1;18(3):745. doi: 10.3390/s18030745.
4
A Fuzzy-Based Approach for Sensing, Coding and Transmission Configuration of Visual Sensors in Smart City Applications.一种基于模糊方法的智慧城市应用中视觉传感器的传感、编码与传输配置
Sensors (Basel). 2017 Jan 5;17(1):93. doi: 10.3390/s17010093.
5
Online least squares one-class support vector machines-based abnormal visual event detection.基于在线最小二乘一类支持向量机的异常视觉事件检测。
Sensors (Basel). 2013 Dec 12;13(12):17130-55. doi: 10.3390/s131217130.
6
Video sensor-based complex scene analysis with Granger causality.基于视频传感器的格兰杰因果关系复杂场景分析。
Sensors (Basel). 2013 Oct 11;13(10):13685-707. doi: 10.3390/s131013685.
7
An intelligent surveillance platform for large metropolitan areas with dense sensor deployment.用于传感器密集部署的大都市的智能监控平台。
Sensors (Basel). 2013 Jun 7;13(6):7414-42. doi: 10.3390/s130607414.
8
The role of advanced sensing in smart cities.先进感测技术在智慧城市中的作用。
Sensors (Basel). 2012 Dec 27;13(1):393-425. doi: 10.3390/s130100393.
IEEE Trans Pattern Anal Mach Intell. 2007 Mar;29(3):411-26. doi: 10.1109/TPAMI.2007.56.
4
Learning semantic scene models from observing activity in visual surveillance.通过观察视觉监控中的活动来学习语义场景模型。
IEEE Trans Syst Man Cybern B Cybern. 2005 Jun;35(3):397-408. doi: 10.1109/tsmcb.2005.846652.
5
Constructing biological knowledge bases by extracting information from text sources.通过从文本来源中提取信息来构建生物知识库。
Proc Int Conf Intell Syst Mol Biol. 1999:77-86.
6
Inverse perspective mapping simplifies optical flow computation and obstacle detection.逆透视映射简化了光流计算和障碍物检测。
Biol Cybern. 1991;64(3):177-85. doi: 10.1007/BF00201978.