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1 Abstract In recent years there h a s b een an increased i n t e r est in the modelling and recognition of human activities involving highly structured and semantically rich behaviour such as dance, aerobics, and sign language. A novel approa c h i s p r esented for automatically acquiring stochastic models of the high-level structure o f an activity(More)
The advent in recent years of robust, real-time, model-based tracking techniques for rigid and non-rigid moving objects has made automated surveillance and event recognition a possibility. We present a statistically based model of object trajectories which is learnt from image sequences. Tra-jectory data is supplied by a tracker using Active Shape Models,(More)
Society's drive toward ever faster socio-technical systems 1-3 , means that there is an urgent need to understand the threat from 'black swan' extreme events that might emerge 4-19. On 6 May 2010, it took just five minutes for a spontaneous mix of human and machine interactions in the global trading cyberspace to generate an unprecedented system-wide Flash(More)
Falls are a major health hazard for the elderly and a major obstacle to independent living. The estimated incidence of falls for both institutionalized and independent persons aged over 75 is at least 30 percent per year. In the SIMBAD (Smart Inactivity Monitor using Array-Based Detectors) project, we've developed an intelligent fall detector based on a(More)
This paper reports on a shared task involving the assignment of ICD-9-CM codes to radiology reports. Two features distinguished this task from previous shared tasks in the biomedical domain. One is that it resulted in the first freely distributable corpus of fully anonymized clinical text. This resource is permanently available and will (we hope) facilitate(More)
We define the Value State Dependence Graph (VSDG). The VSDG is a form of the Value Dependence Graph (VDG) extended by the addition of state dependence edges to model sequentialised computation. These express store dependencies and loop termination dependencies of the original program. We also exploit them to express the additional serialization inherent in(More)
Providing a machine with the ability to learn and use models of natural interaction is a challenging and largely unaddressed problem. A framework is developed enabling both the acquisition of interaction behaviours from the observation of humans, and the use of the acquired behaviour models to simulate a plausible partner during interaction. Statistically(More)
for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Abstract In recent years there has been an increased interest in the modelling and recognition of human activities involving highly structured and semantically rich behaviour(More)
In military planning, it is important to be able to estimate not only the number of fatalities but how often attacks that result in fatalities will take place. We uncovered a simple dynamical pattern that may be used to estimate the escalation rate and timing of fatal attacks. The time difference between fatal attacks by insurgent groups within individual(More)
In recent years there has been an increased interest in the modelling and recognition of human activities involving highly structured and semantically rich behaviour such as dance, aerobics, and sign language. A novel approach is presented for automatically acquiring stochastic models of the high-level structure of an activity without the assumption of any(More)