This paper describes the evolution of our research from video analytics to a
global security system with focus on the video surveillance component. Indeed
video surveillance has evolved from a commodity security tool up to the most
efficient way of tracking perpetrators when terrorism hits our modern urban
centers. As number of cameras soars, one could expect the system to leverage
the huge amount of data carried through the video streams to provide fast
access to video evidences, actionable intelligence for monitoring real-time
events and enabling predictive capacities to assist operators in their
surveillance tasks. This research explores a hybrid platform for video
intelligence capture, automated data extraction, supervised Machine Learning
for intelligently assisted urban video surveillance; Extension to other
components of a global security system are discussed. Applying Knowledge
Management principles in this research helps with deep problem understanding
and facilitates the implementation of efficient information and experience
sharing decision support systems providing assistance to people on the field as
well as in operations centers. The originality of this work is also the
creation of "common" human-machine and machine to machine language and a
security ontology.

描述研究从视频分析到具有全球安全系统的演变，特别关注视频监视组件。本研究探讨了一种混合平台，用于智能辅助城市视频监视的智能捕获、自动化数据提取、监督机器学习；同时还讨论了拓展到全球安全系统的其他组件。