A Spatio-Temporal Methodology for Real-Time Biosurveillance

A Spatio-temporal Methodology for Real-time Biosurveillance

In this paper we introduce a new spatio-temporal methodology for biosurveillance entitled the Repeated Two-sample Rank (RTR) procedure. It is designed to sequentially incorporate information from individual observations and thus can operate on data in real-time as it arrives into an automated biosurveillance system. In addition, upon a signal of a possible outbreak, the methodology suggests a w...

Spatio-temporal texture modelling for real-time crowd anomaly detection

With the rapidly increasing demands from surveillance and security industries, crowd behaviour analysis has become one of the hotly pursued video event detection frontiers within the computer vision arena in recent years. This research has investigated innovative crowd behaviour detection approaches based on statistical crowd features extracted from video footages. In this paper, a new crowd vi...

Telegeomatic System and Real Time Spatio-temporal Database

Telegeomatics, geomatic and telecommunications, is currently in strong growth. Many applications require tools to manage and locate information on mobile data and/or real time. These applications require information processing systems able to exploit spatiotemporal and real time data. These data are issued from sensors and fixed or mobile systems of localization. Current GIS manage and allow ma...

Real-Time Video Dehazing Based on Spatio-Temporal MRF

A Bayesian spatio‐temporal approach for real‐time detection of disease outbreaks: a case study

BACKGROUND For researchers and public health agencies, the complexity of high-dimensional spatio-temporal data in surveillance for large reporting networks presents numerous challenges, which include low signal-to-noise ratios, spatial and temporal dependencies, and the need to characterize uncertainties. Central to the problem in the context of disease outbreaks is a decision structure that re...