Image analysis architectures and techniques for intelligent surveillance systems

Abstract

Video security is becoming more and more important today, as the number of installed cameras can attest. There are many challenging commercial applications to monitor people or vehicle traffic. The work reported here has both research and commercial motivations. Our goals are first to obtain an efficient intelligent system that can meet strong industrial surveillance system requirements and therefore be real-time, distributed, generic and robust. Our second goal is to have a development platform that allows researchers to conceive and easily test new vision algorithms thanks to its modularity and easy setup. This paper focuses on the image analysis modules. It considers the different kind of inputs, algorithm models as well as delay and the need of generality.

Scene analysis for reducing motion JPEG 2000 video surveillance delivery bandwidth and complexity

“…The analysis is based on a real-time statistical segmentation algorithm using a mixture of Gaussians modelling for the background luminance of each pixel [10] [11]. The main advantage is that it automatically supports backgrounds having multiple states like blinking lights, grass and trees moving in the wind, acquisition noise etc.…”

Scalable Video Transmission for a Surveillance System

“…Video surveillance is a significant market [2]. The systems must be networkconnected, entail multiple cameras, and the complete system has to be reliable and robust [2].…”

“…Video surveillance is a significant market [2]. The systems must be networkconnected, entail multiple cameras, and the complete system has to be reliable and robust [2]. Video surveillance applications must be real-time, which entail low delay and timing constraints for processing [2].…”

“…The systems must be networkconnected, entail multiple cameras, and the complete system has to be reliable and robust [2]. Video surveillance applications must be real-time, which entail low delay and timing constraints for processing [2]. Target detection and tracking is a fundamental technology to develop real-world computer vision systems [3].…”

Fiber-Grating-Based Vision System for Real-Time Tracking, Monitoring, and Obstacle Detection

“…These systems should be flexible and have the ability to detect and track moving and stationary targets as a function of time and report their status successfully [1], [2]. Robots need visual information to recognize objects in the working environment [3], [4].…”