Adaptive Fusion Of Particle Filtering And Spatio-Temporal Motion Energy For Human Tracking

Object tracking is an active research area nowadays due to its importance in human computer interface, teleconferencing and video surveillance. However, reliable tracking of objects in the presence of occlusions, pose and illumination changes is still a challenging topic. In this paper, we introduce a novel tracking approach that fuses two cues namely colour and spatio-temporal motion energy within a particle filter based framework. We conduct a measure of coherent motion over two image frames, which reveals the spatio-temporal dynamics of the target. At the same time, the importance of both colour and motion energy cues is determined in the stage of reliability evaluation. This determination helps maintain the performance of the tracking system against abrupt appearance changes. Experimental results demonstrate that the proposed method outperforms the other state of the art techniques in the used test datasets.

Classifying pedestrian movement behaviour from GPS trajectories using visualization and clustering

The quantity and quality of spatial data are increasing rapidly. This is particularly evident in the case of movement data. Devices capable of accurately recording the position of moving entities have become ubiquitous and created an abundance of movement data. Valuable knowledge concerning processes occurring in the physical world can be extracted from these large movement data sets. Geovisual analytics offers powerful techniques to achieve this. This article describes a new geovisual analytics tool specifically designed for movement data. The tool features the classic space-time cube augmented with a novel clustering approach to identify common behaviour. These techniques were used to analyse pedestrian movement in a city environment which revealed the effectiveness of the tool for identifying spatiotemporal patterns. © 2014 Taylor & Francis.

Validation of non‑stationary precipitation series for site‑specific impact assessment: comparison of two statistical downscaling techniques

Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)—two contrasting SD methods—in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector.

Detecting localized homogeneous anomalies over spatio-temporal data

The last decade has witnessed an unprecedented growth in availability of data having spatio-temporal characteristics. Given the scale and richness of such data, finding spatio-temporal patterns that demonstrate significantly different behavior from their neighbors could be of interest for various application scenarios such as – weather modeling, analyzing spread of disease outbreaks, monitoring traffic congestions, and so on. In this paper, we propose an automated approach of exploring and discovering such anomalous patterns irrespective of the underlying domain from which the data is recovered. Our approach differs significantly from traditional methods of spatial outlier detection, and employs two phases – i) discovering homogeneous regions, and ii) evaluating these regions as anomalies based on their statistical difference from a generalized neighborhood. We evaluate the quality of our approach and distinguish it from existing techniques via an extensive experimental evaluation.

Time-lapse Monitoring of the Slopes of a Heritage Earthwork by Means of Near-surface Seismic Techniques

A significant portion of UK’s infrastructures earthworks was built more than 100 years ago, without modern construction standards: poor maintenance and the change of precipitations pattern experienced in the past decades are currently compromising their stability, leading to an increasing number of failures. To address the need for a reliable and time-efficient monitoring of earthworks at risk of failure we propose here the use of two established seismic techniques for the characterization of the near surface, MASW and P-wave refraction. We have regularly collected MASW and P-wave refraction data, from March 2014 to February 2015, along 4 reduced-scale seismic lines located on the flanks of a heritage railway embankment located in Broadway, SW of England. We have observed a definite temporal variability in terms of phase velocities of SW dispersion curves and of P-wave travel times. The accurate choice of ad-hoc inversion strategies has allowed to reconstruct reliable VP and VS models through which it is potentially possible to track the temporal variations of geo-mechanical properties of the embankment slopes. The variability over time of seismic data and seismic velocities seems to correlate well with rainfall data recorded in the days immediately preceding the date of acquisition.

Optical processing devices and techniques for next generation optical networks

Este trabalho surge do interesse em substituir os nós de rede óptica baseados maioritariamente em electrónica por nós de rede baseados em tecnologia óptica. Espera-se que a tecnologia óptica permita maiores débitos binários na rede, maior transparência e maior eficiência através de novos paradigmas de comutação. Segundo esta visão, utilizou-se o MZI-SOA, um dispositivo semicondutor integrado hibridamente, para realizar funcionalidades de processamento óptico de sinal necessárias em nós de redes ópticas de nova geração. Nas novas redes ópticas são utilizados formatos de modulação avançados, com gestão da fase, pelo que foi estudado experimentalmente e por simulação o impacto da utilização destes formatos no desempenho do MZI-SOA na conversão de comprimento de onda e formato, em várias condições de operação. Foram derivadas regras de utilização para funcionamento óptimo. Foi também estudado o impacto da forma dos pulsos do sinal no desempenho do dispositivo. De seguida, o MZI-SOA foi utilizado para realizar funcionalidades temporais ao nível do bit e do pacote. Foi investigada a operação de um conversor de multiplexagem por divisão no comprimento de onda para multiplexagem por divisão temporal óptica, experimentalmente e por simulação, e de um compressor e descompressor de pacotes, por simulação. Para este último, foi investigada a operação com o MZI-SOA baseado em amplificadores ópticos de semicondutor com geometria de poço quântico e ponto quântico. Foi também realizado experimentalmente um ermutador de intervalos temporais que explora o MZI-SOA como conversor de comprimento de onda e usa um banco de linhas de atraso ópticas para introduzir no sinal um atraso seleccionável. Por fim, foi estudado analiticamente, experimentalmente e por simulação o impacto de diafonia em redes ópticas em diversas situações. Extendeu-se um modelo analítico de cálculo de desempenho para contemplar sinais distorcidos e afectados por diafonia. Estudou-se o caso de sinais muito filtrados e afectados por diafonia e mostrou-se que, para determinar correctamente as penalidades que ocorrem, ambos os efeitos devem ser considerados simultaneamente e não em separado. Foi estudada a escalabilidade limitada por diafonia de um comutador de intervalos temporais baseado em MZI-SOA a operar como comutador espacial. Mostrou-se também que sinais afectados fortemente por não-linearidades podem causar penalidades de diafonia mais elevadas do que sinais não afectados por não-linearidades. Neste trabalho foi demonstrado que o MZI-SOA permite construir vários e pertinentes circuitos ópticos, funcionando como bloco fundamental de construção, tendo sido o seu desempenho analisado, desde o nível de componente até ao nível de sistema. Tendo em conta as vantagens e desvantagens do MZI-SOA e os desenvolvimentos recentes de outras tecnologias, foram sugeridos tópicos de investigação com o intuito de evoluir para as redes ópticas de nova geração.

Ressonância magnética em estudos de produção de fala

Estudar os mecanismos subjacentes à produção de fala é uma tarefa complexa e exigente, requerendo a obtenção de dados mediante a utilização de variadas técnicas, onde se incluem algumas modalidades imagiológicas. De entre estas, a Ressonância Magnética (RM) tem ganho algum destaque, nos últimos anos, posicionando-se como uma das mais promissoras no domínio da produção de fala. Um importante contributo deste trabalho prende-se com a otimização e implementação de protocolos (RM) e proposta de estratégias de processamento de imagem ajustados aos requisitos da produção de fala, em geral, e às especificidades dos diferentes sons. Para além disso, motivados pela escassez de dados para o Português Europeu (PE), constitui-se como objetivo a obtenção de dados articulatórios que permitam complementar informação já existente e clarificar algumas questões relativas à produção dos sons do PE (nomeadamente, consoantes laterais e vogais nasais). Assim, para as consoantes laterais foram obtidas imagens RM (2D e 3D), através de produções sustidas, com recurso a uma sequência Eco de Gradiente (EG) rápida (3D VIBE), no plano sagital, englobando todo o trato vocal. O corpus, adquirido por sete falantes, contemplou diferentes posições silábicas e contextos vocálicos. Para as vogais nasais, foram adquiridas, em três falantes, imagens em tempo real com uma sequência EG - Spoiled (TurboFLASH), nos planos sagital e coronal, obtendo-se uma resolução temporal de 72 ms (14 frames/s). Foi efetuada aquisição sincronizada das imagens com o sinal acústico mediante utilização de um microfone ótico. Para o processamento e análise de imagem foram utilizados vários algoritmos semiautomáticos. O tratamento e análise dos dados permitiu efetuar uma descrição articulatória das consoantes laterais, ancorada em dados qualitativos (e.g., visualizações 3D, comparação de contornos) e quantitativos que incluem áreas, funções de área do trato vocal, extensão e área das passagens laterais, avaliação de efeitos contextuais e posicionais, etc. No que respeita à velarização da lateral alveolar /l/, os resultados apontam para um /l/ velarizado independentemente da sua posição silábica. Relativamente ao /L/, em relação ao qual a informação disponível era escassa, foi possível verificar que a sua articulação é bastante mais anteriorizada do que tradicionalmente descrito e também mais extensa do que a da lateral alveolar. A resolução temporal de 72 ms conseguida com as aquisições de RM em tempo real, revelou-se adequada para o estudo das características dinâmicas das vogais nasais, nomeadamente, aspetos como a duração do gesto velar, gesto oral, coordenação entre gestos, etc. complementando e corroborando resultados, já existentes para o PE, obtidos com recurso a outras técnicas instrumentais. Para além disso, foram obtidos novos dados de produção relevantes para melhor compreensão da nasalidade (variação área nasal/oral no tempo, proporção nasal/oral). Neste estudo, fica patente a versatilidade e potencial da RM para o estudo da produção de fala, com contributos claros e importantes para um melhor conhecimento da articulação do Português, para a evolução de modelos de síntese de voz, de base articulatória, e para aplicação futura em áreas mais clínicas (e.g., perturbações da fala).

Soft-computing techniques applied to artificial tissue temperature estimation

Tese dout., Engenharia electrónica e computação - Processamento de sinal, Universidade do Algarve, 2008

Open-domain web-based multiple document : question answering for list questions with support for temporal restrictors

Tese de doutoramento, Informática (Ciências da Computação), Universidade de Lisboa, Faculdade de Ciências, 2015

A forma do tempo : a timeline interativa como meio de visualização temporal

This thesis takes a theoretical and practical approach to data visualization, focusing in particular on interactive timelines as a means to mapping historical/cultural narratives. It seeks to understand how timelines can efficiently communicate a historical narrative, enhancing the topic’s comprehension whilst relating it to the surrounding context. For this purpose, an interactive timeline on Design in Portugal from 1900 to present, was conceptualized and developed. The research adopted a descriptive methodology. The theoretical framework depicts the basic concepts, models and taxonomies associated to timelines, which derive from the main studies available on the matter. From this, a model for the analysis of three case studies – Idea Line (2002), The Path of Protest (2011) and British History Timeline (2006) – was proposed. The selection criteria shows that they refer to interactive timelines depicting a historical narrative, in addition to being as heterogeneous as possible with respect to the themes presented and conveyed purposes. The comparative analysis produced a set of thoughts, conclusions and principles, subsequently considered and applied in the development of the timeline presented. The results of this study point to the decisive role of visual setup of the time axis and user tasks in the interpretation of information. The effective implementation of the timeline Design in Portugal: from 1900 to present, contributes to the study of timelines as information devices with its own characteristics and capabilities, promotes associated research and theoretical systematization and, on a pragmatic note, helps creating the basis for the gathering, compilation and presentation of relevant information on design in Portugal, providing the academic and professional community with an effective tool for referring and learning

Multidimensional scaling visualization of earthquake phenomena

Earthquakes are associated with negative events, such as large number of casualties, destruction of buildings and infrastructures, or emergence of tsunamis. In this paper, we apply the Multidimensional Scaling (MDS) analysis to earthquake data. MDS is a set of techniques that produce spatial or geometric representations of complex objects, such that, objects perceived to be similar/distinct in some sense are placed nearby/distant on the MDS maps. The interpretation of the charts is based on the resulting clusters since MDS produces a different locus for each similarity measure. In this study, over three million seismic occurrences, covering the period from January 1, 1904 up to March 14, 2012 are analyzed. The events, characterized by their magnitude and spatiotemporal distributions, are divided into groups, either according to the Flinn–Engdahl seismic regions of Earth or using a rectangular grid based in latitude and longitude coordinates. Space-time and Space-frequency correlation indices are proposed to quantify the similarities among events. MDS has the advantage of avoiding sensitivity to the non-uniform spatial distribution of seismic data, resulting from poorly instrumented areas, and is well suited for accessing dynamics of complex systems. MDS maps are proven as an intuitive and useful visual representation of the complex relationships that are present among seismic events, which may not be perceived on traditional geographic maps. Therefore, MDS constitutes a valid alternative to classic visualization tools, for understanding the global behavior of earthquakes.

Dynamical Analysis and Visualization of Tornadoes Time Series

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.

Land cover mapping analysis and urban growth modeling using remote sensing techniques

The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectively.

Analysis and visualization of energy use for university campus

The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.

Temporal SNR characteristics in segmented 3D-EPI at 7T.

Three-dimensional segmented echo planar imaging (3D-EPI) is a promising approach for high-resolution functional magnetic resonance imaging, as it provides an increased signal-to-noise ratio (SNR) at similar temporal resolution to traditional multislice 2D-EPI readouts. Recently, the 3D-EPI technique has become more frequently used and it is important to better understand its implications for fMRI. In this study, the temporal SNR characteristics of 3D-EPI with varying numbers of segments are studied. It is shown that, in humans, the temporal variance increases with the number of segments used to form the EPI acquisition and that for segmented acquisitions, the maximum available temporal SNR is reduced compared to single shot acquisitions. This reduction with increased segmentation is not found in phantom data and thus likely due to physiological processes. When operating in the thermal noise dominated regime, fMRI experiments with a motor task revealed that the 3D variant outperforms the 2D-EPI in terms of temporal SNR and sensitivity to detect activated brain regions. Thus, the theoretical SNR advantage of a segmented 3D-EPI sequence for fMRI only exists in a low SNR situation. However, other advantages of 3D-EPI, such as the application of parallel imaging techniques in two dimensions and the low specific absorption rate requirements, may encourage the use of the 3D-EPI sequence for fMRI in situations with higher SNR.