Results 1 - 10 of 591

Spatio-temporal Shadow Segmentation and Tracking

by Elena Salvador, Andrea Cavallaro, Touradj Ebrahimi - in Proc. of Visual Communications and Image Processing , 2003
"... Shadow segmentation is a critical issue for systems aiming at extracting, tracking or recognizing objects in a given scene. Shadows can in fact modify the shape and colour of objects and therefore affect scene analysis and interpretation systems in many applications, such as video database search an ..."
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be reliably computed for shadows. Therefore shadows may be described only by a limited amount of information. The proposed tracking algorithm makes use of this information and provides a reliability estimation of shadow recognition results of the first stage over time. This temporal analysis eliminates

Mitigating Spam Using Spatio-Temporal Reputation

by Andrew G. West, Adam J. Aviv, Jian Chang, Insup Lee , 2010
"... In this paper we present Preventive Spatio-Temporal Aggregation (PRESTA), a reputation model that combines spatial and temporal features to produce values that are behavior predictive and useful in partial-knowledge situations. To evaluate its effectiveness, we applied PRESTA in the domain of spam d ..."
Abstract - Cited by 9 (8 self) - Add to MetaCart
In this paper we present Preventive Spatio-Temporal Aggregation (PRESTA), a reputation model that combines spatial and temporal features to produce values that are behavior predictive and useful in partial-knowledge situations. To evaluate its effectiveness, we applied PRESTA in the domain of spam

Bayesian modelling and analysis of spatio-temporal neuronal networks

by Fabio Rigat Y, Mathisca De Gunst Z , 2005
"... Abstract: This paper illustrates a novel dynamic Bayesian network for stochastic integrate-and-re neuronal systems. We adopt a Bayesian hierarchical perspective to introduce at dierent model stages the parameters characterizing the neuronal spiking process over a discrete time grid, the unknown stru ..."
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Abstract: This paper illustrates a novel dynamic Bayesian network for stochastic integrate-and-re neuronal systems. We adopt a Bayesian hierarchical perspective to introduce at dierent model stages the parameters characterizing the neuronal spiking process over a discrete time grid, the unknown

A Framework of Spatio-Temporal Analysis for Video

by Duan-yu Chen A, Kevin Cannons B, Hsiao-rong Tyan C
"... Abstract—This paper presents a video surveillance system that is capable of detecting and classifying moving targets in real-time. The system extracts moving targets from a video stream and classifies them into predefined categories according to their spatiotemporal properties. Classification of the ..."
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Abstract—This paper presents a video surveillance system that is capable of detecting and classifying moving targets in real-time. The system extracts moving targets from a video stream and classifies them into predefined categories according to their spatiotemporal properties. Classification

Filtering nonlinear spatio-temporal chaos with autoregressive linear stochastic models

by Emily L Kang , John Harlim - Physica D: Nonlinear Phenomena, 241(12):1099 – 1113 , 2012
"... Abstract Fundamental barriers in practical filtering of nonlinear spatio-temporal chaotic systems are model errors attributed to the stiffness in resolving multiscale features. Recently, reduced stochastic filters based on linear stochastic models have been introduced to overcome such stiffness; on ..."
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Abstract Fundamental barriers in practical filtering of nonlinear spatio-temporal chaotic systems are model errors attributed to the stiffness in resolving multiscale features. Recently, reduced stochastic filters based on linear stochastic models have been introduced to overcome such stiffness

Model-checking algorithms for continuous-time Markov chains

by Christel Baier, Boudewijn Haverkort, Holger Hermanns, Joost-Pieter Katoen - IEEE TRANSACTIONS ON SOFTWARE ENGINEERING , 2003
"... Continuous-time Markov chains (CTMCs) have been widely used to determine system performance and dependability characteristics. Their analysis most often concerns the computation of steady-state and transient-state probabilities. This paper introduces a branching temporal logic for expressing real-t ..."
Abstract - Cited by 235 (48 self) - Add to MetaCart
Continuous-time Markov chains (CTMCs) have been widely used to determine system performance and dependability characteristics. Their analysis most often concerns the computation of steady-state and transient-state probabilities. This paper introduces a branching temporal logic for expressing real

SPATIO-TEMPORAL POINT PATTERN ANALYSIS USING GENETIC ALGORITHMS

by Yorgos N. Photis, Yorgos Graikousis
"... The efficiency of emergency service systems is measured in terms of their ability to deploy units and personnel in a timely and effective manner upon an event’s occurrence. Aiming to exploit stochastic demand, spatial tracing and location analysis of emergency incidents are examined through the util ..."
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spatio-temporal clustering of demand, definition of the relevant centres, formulation of possible future states of the system and finally, definition of locational strategies for the improvement of the provided services.

2002: A spatio-temporal approach for global validation and analysis of MODIS aerosol products. Geophys

by Charles Ichoku, D. Allen Chu, Shana Mattoo, Yoram J. Kaufman, Lorraine A. Remer, Didier Tanré, Ilya Slutsker, Brent N. Holben - Res. Lett , 2003
"... new data sets of the global distribution and properties of aerosol are being retrieved, and need to be validated and analyzed. A system has been put in place to generate spatial statistics (mean, standard deviation, direction and rate of spatial variation, and spatial correlation coefficient) of the ..."
Abstract - Cited by 61 (12 self) - Add to MetaCart
new data sets of the global distribution and properties of aerosol are being retrieved, and need to be validated and analyzed. A system has been put in place to generate spatial statistics (mean, standard deviation, direction and rate of spatial variation, and spatial correlation coefficient

SIMPLE QUANTITATIVE ANALYSIS OF SPATIO-TEMPORAL DIAGRAMS FOR DOMAIN WALL DYNAMICS

by R A Kosiński , R Stępień , 1995
"... A quantitative analysis of spatio-temporal diagrams, which describe the dynamics of a chosen, spatially extended dynamic system (a domain wall in a thin magnetic garnet film) is presented. Two quantifiers characterizing such diagrams -a correlation function and power spectrum density functionwere c ..."
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calculated using solutions of equations of motion. It was found that introducing these quantifiers to the analysis of spatio-temporal diagrams enables one to effectively characterize the type and the properties of motion of the considered system.

Estimation and Characterization of Nonlinear Behavior of Nonlinear Spatio-Temporal Systems

by Xingjian Jing, Hanwen Ning, Li Cheng
"... Traditional methods for the analysis of a PDE system rely on an analytical solution of the system, which is difficult to obtain for most nonlinear PDEs. Alternative methods such as qualitative analysis of solutions or numerical methods for an approximation are studied using functional analysis and g ..."
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and generalized function theory [2], or finite element methods and difference methods [3]. Identification of STSs has also been studied recently using finite dimensional parametric MIMO models to approximate infinite dimensional systems [4]. The estimation of spatio-temporal systems is formulated into a
Results 1 - 10 of 591