Detection of dynamic background due to swaying movements from motion features

Dynamically changing background (dynamic background) still presents a great challenge to many motion-based video surveillance systems. In the context of event detection, it is a major source of false alarms. There is a strong need from the security industry either to detect and suppress these false alarms, or dampen the effects of background changes, so as to increase the sensitivity to meaningful events of interest. In this paper, we restrict our focus to one of the most common causes of dynamic background changes: 1) that of swaying tree branches and 2) their shadows under windy conditions. Considering the ultimate goal in a video analytics pipeline, we formulate a new dynamic background detection problem as a signal processing alternative to the previously described but unreliable computer vision-based approaches. Within this new framework, we directly reduce the number of false alarms by testing if the detected events are due to characteristic background motions. In addition, we introduce a new data set suitable for the evaluation of dynamic background detection. It consists of real-world events detected by a commercial surveillance system from two static surveillance cameras. The research question we address is whether dynamic background can be detected reliably and efficiently using simple motion features and in the presence of similar but meaningful events, such as loitering. Inspired by the tree aerodynamics theory, we propose a novel method named local variation persistence (LVP), that captures the key characteristics of swaying motions. The method is posed as a convex optimization problem, whose variable is the local variation. We derive a computationally efficient algorithm for solving the optimization problem, the solution of which is then used to form a powerful detection statistic. On our newly collected data set, we demonstrate that the proposed LVP achieves excellent detection results and outperforms the best alternative adapted from existing art in the dynamic background literature.

K-Center: an approach on the multi-source identification of information diffusion

The global diffusion of epidemics, computer viruses, and rumors causes great damage to our society. It is critical to identify the diffusion sources and timely quarantine them. However, most methods proposed so far are unsuitable for diffusion with multiple sources because of the high computational cost and the complex spatiotemporal diffusion processes. In this paper, based on the knowledge of infected nodes and their connections, we propose a novel method to identify multiple diffusion sources, which can address three main issues in this area: 1) how many sources are there? 2) where did the diffusion emerge? and 3) when did the diffusion break out? We first derive an optimization formulation for multi-source identification problem. This is based on altering the original network into a new network concerning two key elements: 1) propagation probability and 2) the number of hops between nodes. Experiments demonstrate that the altered network can accurately reflect the complex diffusion processes with multiple sources. Second, we derive a fast method to optimize the formulation. It has been proved that the proposed method is convergent and the computational complexity is O(mn log α) , where α = α (m,n) is the slowly growing inverse-Ackermann function, n is the number of infected nodes, and m is the number of edges connecting them. Finally, we introduce an efficient algorithm to estimate the spreading time and the number of diffusion sources. To evaluate the proposed method, we compare the proposed method with many competing methods in various real-world network topologies. Our method shows significant advantages in the estimation of multiple sources and the prediction of spreading time.

Estudo da transformada rápida wavelet e sua conexão com banco de filtros

In this work we presented an exhibition of the mathematical theory of orthogonal compact support wavelets in the context of multiresoluction analysis. These are particularly attractive wavelets because they lead to a stable and very efficient algorithm, that is Fast Transform Wavelet (FWT). One of our objectives is to develop efficient algorithms for calculating the coefficients wavelet (FWT) through the pyramid algorithm of Mallat and to discuss his connection with filters Banks. We also studied the concept of multiresoluction analysis, that is the context in that wavelets can be understood and built naturally, taking an important step in the change from the Mathematical universe (Continuous Domain) for the Universe of the representation (Discret Domain)

Métodos numéricos para resolução de equações diferenciais ordinárias lineares baseados em interpolação por spline

In this work we have elaborated a spline-based method of solution of inicial value problems involving ordinary differential equations, with emphasis on linear equations. The method can be seen as an alternative for the traditional solvers such as Runge-Kutta, and avoids root calculations in the linear time invariant case. The method is then applied on a central problem of control theory, namely, the step response problem for linear EDOs with possibly varying coefficients, where root calculations do not apply. We have implemented an efficient algorithm which uses exclusively matrix-vector operations. The working interval (till the settling time) was determined through a calculation of the least stable mode using a modified power method. Several variants of the method have been compared by simulation. For general linear problems with fine grid, the proposed method compares favorably with the Euler method. In the time invariant case, where the alternative is root calculation, we have indications that the proposed method is competitive for equations of sifficiently high order.

Modelo numérico do terreno obtido por diferentes métodos em cartas planialtimétricas

The digital elevation model is important to determine the slope and land use capability, therefore, a proposal of methodology for acquisition of elevation data contemplating an efficient algorithm to generate a slope map was developed. Thus, it was aimed to obtain and evaluate a digital elevation model without the vetorization of the contours on planialtimetric charts. The area for acquisition of elevation data was Sao Manuel, SP. The data were collected by two methods: level contour vetorization and the gathering of elevation points on the level contour with maximum elevation points. The elevation data were analyzed by geostatistical techniques. Inspite of wide difference in the number of collected points between two methods, the variograms were adjusted to the exponential model and showed a range of approximately 1500 m, which does not justify the wide difficulty in vetorization of the planialtimetric charts, once the data points collected in the area were appropriately distributed, they represented rightly the terrain surface.

Evolutionary heuristic to determine future land use

In the spatial electric load forecasting, the future land use determination is one of the most important tasks, and one of the most difficult, because of the stochastic nature of the city growth. This paper proposes a fast and efficient algorithm to find out the future land use for the vacant land in the utility service area, using ideas from knowledge extraction and evolutionary algorithms. The methodology was implemented into a full simulation software for spatial electric load forecasting, showing a high rate of success when the results are compared to information gathered from specialists. The importance of this methodology lies in the reduced set of data needed to perform the task and the simplicity for implementation, which is a great plus for most of the electric utilities without specialized tools for this planning activity. © 2008 IEEE.

Tomografia eletromagnética para caracterização de reservatórios de hidrocarbonetos

Na produção de petróleo é importante o monitoramento dos parâmetros do reservatório (permeabilidade, porosidade, saturação, pressão, etc) para o seu posterior gerenciamento. A variação dos parâmetros dinâmicos do reservatório induz variações na dinâmica do fluxo no reservatório, como por exemplo, perdas na pressão, dificultando o processo de extração do óleo. A injeção de fluidos aumenta a energia interna do reservatório e incrementa a pressão, estimulando o movimento do óleo em direção aos poços de extração. A tomografia eletromagnética poço-a-poço pode se tomar em uma técnica bastante eficaz no monitoramento dos processos de injeção, considerando-se o fato de ser altamente detectável a percolação de fluidos condutivos através das rochas. Esta tese apresenta o resultado de um algoritmo de tomografia eletromagnética bastante eficaz aplicado a dados sintéticos. O esquema de imageamento assume uma simetria cilíndrica em torno de uma fonte constituída por um dipolo magnético. Durante o processo de imageamento foram usados 21 transmissores e 21 receptores distribuídos em dois poços distanciados de 100 metros. O problema direto foi resolvido pelo método dos elementos finitos aplicado à equação de Helmhotz do campo elétrico secundário. O algoritmo resultante é válido para qualquer situação, não estando sujeito às restrições impostas aos algoritmos baseados nas aproximações de Born e Rytov. Por isso, pode ser aplicado eficientemente em qualquer situação, como em meios com contrastes de condutividade elétrica variando de 2 a 100, freqüências de 0.1 a 1000.0 kHz e heterogeneidades de qualquer dimensão. O problema inverso foi resolvido por intermédio do algoritmo de Marquardt estabilizado. A solução é obtida iterativamente. Os dados invertidos, com ruído Gaussiano aditivo, são as componentes em fase e em quadratura do campo magnético vertical. Sem o uso de vínculos o problema é totalmente instável, resultando em imagens completamente borradas. Duas categorias de vínculos foram usadas: vínculos relativos, do tipo suavidade, e vínculos absolutos. Os resultados obtidos mostram a eficiência desses dois tipos de vínculos através de imagens nítidas de alta resolução. Os tomogramas mostram que a resolução é melhor na direção vertical do que na horizontal e que é também função da freqüência. A posição e a atitude da heterogeneidade é bem recuperada. Ficou também demonstrado que a baixa resolução horizontal pode ser atenuada ou até mesmo eliminada por intermédio dos vínculos.

Uma abordagem híbrida e semiautomática para estimativa de regiões cobertas por nuvens e sombras em imagens de satélite: análise e avaliação

Os principais objetivos deste trabalho são propor um algoritmo eficiente e o mais automático possível para estimar o que está coberto por regiões de nuvens e sombras em imagens de satélite; e um índice de confiabilidade, que seja aplicado previamente à imagem, visando medir a viabilidade da estimação das regiões cobertas pelos componentes atmosféricos usando tal algoritmo. A motivação vem dos problemas causados por esses elementos, entre eles: dificultam a identificação de objetos de imagem, prejudicam o monitoramento urbano e ambiental, e desfavorecem etapas cruciais do processamento digital de imagens para extrair informações ao usuário, como segmentação e classificação. Através de uma abordagem híbrida, é proposto um método para decompor regiões usando um filtro passa-baixas não-linear de mediana, a fim de mapear as regiões de estrutura (homogêneas), como vegetação, e de textura (heterogêneas), como áreas urbanas, na imagem. Nessas áreas, foram aplicados os métodos de restauração Inpainting por suavização baseado em Transformada Cosseno Discreta (DCT), e Síntese de Textura baseada em modelos, respectivamente. É importante salientar que as técnicas foram modificadas para serem capazes de trabalhar com imagens de características peculiares que são obtidas por meio de sensores de satélite, como por exemplo, as grandes dimensões e a alta variação espectral. Já o índice de confiabilidade, tem como objetivo analisar a imagem que contém as interferências atmosféricas e daí estimar o quão confiável será a redefinição com base no percentual de cobertura de nuvens sobre as regiões de textura e estrutura. Tal índice é composto pela combinação do resultado de algoritmos supervisionados e não-supervisionados envolvendo 3 métricas: Exatidão Global Média (EGM), Medida De Similaridade Estrutural (SSIM) e Confiança Média Dos Pixels (CM). Finalmente, verificou-se a eficácia destas metodologias através de uma avaliação quantitativa (proporcionada pelo índice) e qualitativa (pelas imagens resultantes do processamento), mostrando ser possível a aplicação das técnicas para solucionar os problemas que motivaram a realização deste trabalho.

Estimation of croplands using indicator kriging and fuzzy classification

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Implementation of a non ground meta interpreter for defeasible logic

Human reasoning is a fascinating and complex cognitive process that can be applied in different research areas such as philosophy, psychology, laws and financial. Unfortunately, developing supporting software (to those different areas) able to cope such as complex reasoning it’s difficult and requires a suitable logic abstract formalism. In this thesis we aim to develop a program, that has the job to evaluate a theory (a set of rules) w.r.t. a Goal, and provide some results such as “The Goal is derivable from the KB5 (of the theory)”. In order to achieve this goal we need to analyse different logics and choose the one that best meets our needs. In logic, usually, we try to determine if a given conclusion is logically implied by a set of assumptions T (theory). However, when we deal with programming logic we need an efficient algorithm in order to find such implications. In this work we use a logic rather similar to human logic. Indeed, human reasoning requires an extension of the first order logic able to reach a conclusion depending on not definitely true6 premises belonging to a incomplete set of knowledge. Thus, we implemented a defeasible logic7 framework able to manipulate defeasible rules. Defeasible logic is a non-monotonic logic designed for efficient defeasible reasoning by Nute (see Chapter 2). Those kind of applications are useful in laws area especially if they offer an implementation of an argumentation framework that provides a formal modelling of game. Roughly speaking, let the theory is the set of laws, a keyclaim is the conclusion that one of the party wants to prove (and the other one wants to defeat) and adding dynamic assertion of rules, namely, facts putted forward by the parties, then, we can play an argumentative challenge between two players and decide if the conclusion is provable or not depending on the different strategies performed by the players. Implementing a game model requires one more meta-interpreter able to evaluate the defeasible logic framework; indeed, according to Göedel theorem (see on page 127), we cannot evaluate the meaning of a language using the tools provided by the language itself, but we need a meta-language able to manipulate the object language8. Thus, rather than a simple meta-interpreter, we propose a Meta-level containing different Meta-evaluators. The former has been explained above, the second one is needed to perform the game model, and the last one will be used to change game execution and tree derivation strategies.

Simulations of physics and chemistry of polar stratospheric clouds with a general circulation model

A polar stratospheric cloud submodel has been developed and incorporated in a general circulation model including atmospheric chemistry (ECHAM5/MESSy). The formation and sedimentation of polar stratospheric cloud (PSC) particles can thus be simulated as well as heterogeneous chemical reactions that take place on the PSC particles. For solid PSC particle sedimentation, the need for a tailor-made algorithm has been elucidated. A sedimentation scheme based on first order approximations of vertical mixing ratio profiles has been developed. It produces relatively little numerical diffusion and can deal well with divergent or convergent sedimentation velocity fields. For the determination of solid PSC particle sizes, an efficient algorithm has been adapted. It assumes a monodisperse radii distribution and thermodynamic equilibrium between the gas phase and the solid particle phase. This scheme, though relatively simple, is shown to produce particle number densities and radii within the observed range. The combined effects of the representations of sedimentation and solid PSC particles on vertical H2O and HNO3 redistribution are investigated in a series of tests. The formation of solid PSC particles, especially of those consisting of nitric acid trihydrate, has been discussed extensively in recent years. Three particle formation schemes in accordance with the most widely used approaches have been identified and implemented. For the evaluation of PSC occurrence a new data set with unprecedented spatial and temporal coverage was available. A quantitative method for the comparison of simulation results and observations is developed and applied. It reveals that the relative PSC sighting frequency can be reproduced well with the PSC submodel whereas the detailed modelling of PSC events is beyond the scope of coarse global scale models. In addition to the development and evaluation of new PSC submodel components, parts of existing simulation programs have been improved, e.g. a method for the assimilation of meteorological analysis data in the general circulation model, the liquid PSC particle composition scheme, and the calculation of heterogeneous reaction rate coefficients. The interplay of these model components is demonstrated in a simulation of stratospheric chemistry with the coupled general circulation model. Tests against recent satellite data show that the model successfully reproduces the Antarctic ozone hole.

Exact computation of the adjacency graph of an arrangement of quadrics

Präsentiert wird ein vollständiger, exakter und effizienter Algorithmus zur Berechnung des Nachbarschaftsgraphen eines Arrangements von Quadriken (Algebraische Flächen vom Grad 2). Dies ist ein wichtiger Schritt auf dem Weg zur Berechnung des vollen 3D Arrangements. Dabei greifen wir auf eine bereits existierende Implementierung zur Berechnung der exakten Parametrisierung der Schnittkurve von zwei Quadriken zurück. Somit ist es möglich, die exakten Parameterwerte der Schnittpunkte zu bestimmen, diese entlang der Kurven zu sortieren und den Nachbarschaftsgraphen zu berechnen. Wir bezeichnen unsere Implementierung als vollständig, da sie auch die Behandlung aller Sonderfälle wie singulärer oder tangentialer Schnittpunkte einschließt. Sie ist exakt, da immer das mathematisch korrekte Ergebnis berechnet wird. Und schließlich bezeichnen wir unsere Implementierung als effizient, da sie im Vergleich mit dem einzigen bisher implementierten Ansatz gut abschneidet. Implementiert wurde unser Ansatz im Rahmen des Projektes EXACUS. Das zentrale Ziel von EXACUS ist es, einen Prototypen eines zuverlässigen und leistungsfähigen CAD Geometriekerns zu entwickeln. Obwohl wir das Design unserer Bibliothek als prototypisch bezeichnen, legen wir dennoch größten Wert auf Vollständigkeit, Exaktheit, Effizienz, Dokumentation und Wiederverwendbarkeit. Über den eigentlich Beitrag zu EXACUS hinaus, hatte der hier vorgestellte Ansatz durch seine besonderen Anforderungen auch wesentlichen Einfluss auf grundlegende Teile von EXACUS. Im Besonderen hat diese Arbeit zur generischen Unterstützung der Zahlentypen und der Verwendung modularer Methoden innerhalb von EXACUS beigetragen. Im Rahmen der derzeitigen Integration von EXACUS in CGAL wurden diese Teile bereits erfolgreich in ausgereifte CGAL Pakete weiterentwickelt.

Automatic Deployment of Applications in the Cloud

In distributed systems like clouds or service oriented frameworks, applications are typically assembled by deploying and connecting a large number of heterogeneous software components, spanning from fine-grained packages to coarse-grained complex services. The complexity of such systems requires a rich set of techniques and tools to support the automation of their deployment process. By relying on a formal model of components, a technique is devised for computing the sequence of actions allowing the deployment of a desired configuration. An efficient algorithm, working in polynomial time, is described and proven to be sound and complete. Finally, a prototype tool implementing the proposed algorithm has been developed. Experimental results support the adoption of this novel approach in real life scenarios.

Portfolio Approaches in Constraint Programming

Recent research has shown that the performance of a single, arbitrarily efficient algorithm can be significantly outperformed by using a portfolio of —possibly on-average slower— algorithms. Within the Constraint Programming (CP) context, a portfolio solver can be seen as a particular constraint solver that exploits the synergy between the constituent solvers of its portfolio for predicting which is (or which are) the best solver(s) to run for solving a new, unseen instance. In this thesis we examine the benefits of portfolio solvers in CP. Despite portfolio approaches have been extensively studied for Boolean Satisfiability (SAT) problems, in the more general CP field these techniques have been only marginally studied and used. We conducted this work through the investigation, the analysis and the construction of several portfolio approaches for solving both satisfaction and optimization problems. We focused in particular on sequential approaches, i.e., single-threaded portfolio solvers always running on the same core. We started from a first empirical evaluation on portfolio approaches for solving Constraint Satisfaction Problems (CSPs), and then we improved on it by introducing new data, solvers, features, algorithms, and tools. Afterwards, we addressed the more general Constraint Optimization Problems (COPs) by implementing and testing a number of models for dealing with COP portfolio solvers. Finally, we have come full circle by developing sunny-cp: a sequential CP portfolio solver that turned out to be competitive also in the MiniZinc Challenge, the reference competition for CP solvers.

TRIO LOGIC REGRESSION - DETECTION OF SNP - SNP INTERACTIONS IN CASE-PARENT TRIOS

Statistical approaches to evaluate higher order SNP-SNP and SNP-environment interactions are critical in genetic association studies, as susceptibility to complex disease is likely to be related to the interaction of multiple SNPs and environmental factors. Logic regression (Kooperberg et al., 2001; Ruczinski et al., 2003) is one such approach, where interactions between SNPs and environmental variables are assessed in a regression framework, and interactions become part of the model search space. In this manuscript we extend the logic regression methodology, originally developed for cohort and case-control studies, for studies of trios with affected probands. Trio logic regression accounts for the linkage disequilibrium (LD) structure in the genotype data, and accommodates missing genotypes via haplotype-based imputation. We also derive an efficient algorithm to simulate case-parent trios where genetic risk is determined via epistatic interactions.