A Compression Algorithm for Video Surveillance System

A S.O.M. Based Algorithm for Video Surveillance System Parameter

In automatic video surveillance systems, full time monitoring represents an important goal to achieve. The aim of this paper is to find out a new methodology for video surveillance adaptive parameter regulation. The method presented here is based upon Self Organizing Map (S.O.M.) which are used for parameter regulation purposes. Results shown in this paper prove how this method permit to achiev...

Video analysis and compression for surveillance applications

Smoke detection algorithm for intelligent video surveillance system

An efficient smoke detection algorithm on color video sequences obtained from a stationary camera is proposed. Our algorithm considers dynamic and static features of smoke and is composed of basic steps: preprocessing; slowly moving areas and pixels segmentation in a current input frame based on adaptive background subtraction; merge slowly moving areas with pixels into blobs; classification of...

Video Compression and Data Flow for Video Surveillance Whitepaper

Executive Summary The desire for increased security has catapulted the popularity of video surveillance systems, which are now widely deployed in places such as airports, banks, public transportation centers and even private homes. The many problems associated with traditional analog-based systems are influencing the push for digital-based systems. Furthermore, with the growing popularity of co...

A System for Video Surveillance and Monitoring

The Robotics Institute at Carnegie Mellon University (CMU) and the Sarnoff Corporation are developing a system for autonomous Video Surveillance and Monitoring. The technical objective is to use multiple, cooperative video sensors to provide continuous coverage of people and vehicles in cluttered environments. This paper presents an overview of the system and significant results achieved to date.