Intelligent Video Surveillance System Architecture for Abnormal Activity Detection

Video security is becoming more and more vital today due to rapid development of hardware equipments as the number of installed cameras can confirm. This paper presents the system architecture of IVSS, an Intelligent Video Surveillance System based on IPcameras and deployed in an academic environment. In fact, Video surveillance is increasingly found in academic institutions. It is used to oversee the safety of teachers and students, as well as to protect assets from vandalism and theft. In this work the surveillance system is deployed in our university environment, it is based on a set of digital IP video cameras linked by the university IP network infrastructure. Our system architecture is based on efficient moving object detecting and tracking algorithm and a robust statistical activity recognition framework based on SVM which is used for modeling activities. The experimental results on real-time video streams show the feasibility of our system and its effectiveness in human activity recognition.