148 research outputs found

    Codage vidéo par schéma lifting avec gestion des occlusions

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    · Le schéma lifting compensé en mouvement est utilisé dans la plupart des codeurs vidéo basés ondelettes. Cependant, l'estimation et la compensation de mouvement à l'aide de blocs entraîne l'apparition d'artéfacts visibles autour des objets en mouvement et du bord des images. Dans ce papier, nous proposons une nouvelle méthode de filtrage temporel qui fait appel à une segmentation et une estimation de mouvement conjointes. Le principe consiste à attribuer un mouvement à des régions de forme adaptable au lieu d'utiliser des blocs. Nous présentons d'une part l'algorithme de filtrage «Puzzle» et étudions les conditions de son inversibilité. D'autre part, nous proposons une méthode d'extraction des régions d'occlusion à partir des informations de segmentation et de mouvement; ces régions sont ensuite utilisées pour gérer les occlusions. Les premiers résultats expérimentaux confirme la diminution des effets de blocs; la bonne gestion des occlusions permet une baisse significative de l'entropie des sous-bandes temporelles

    EEG and ECG nonlinear and spectral multiband analysis to explore the effect of videogames against anxiety

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    Currently, the use of video games has purposes that go beyond entertainment and has been gaining prominence in the health area. In this sense, it was hypothesized that it is possible to discriminate biological signals, namely electrocardiographic and electroencephalographic signals, collected from different participants stimulated through three different commercial video games, Tetris, Bejeweled and Energy. To test this hypothesis, a protocol was developed with the Trier Social Stress Test to induce and dose stress in the subjects to similar levels before each game session, in order to observe the effects of the three test games (3 study groups) at the physiological level. Initially collected at 2000 Hz, the signals were resampled to 500 Hz and filtered using a Butterworth low-pass filter. After filtering the signals, several representative features of the study signals were collected. These features consisted of a series of nonlinear metrics such as the Lyapunov exponent and Correlation Dimension, self-similarity metrics such as the Hurst exponent, and detrended fluctuation analysis, fractal dimensions - such as the Katz and Higuchi fractal dimensions - and metrics of signal chaos and activity, such as signal energy, Logarithmic entropy and Shannon entropy, and a number of spectral metrics for the EEG signal, which should be able to help identify any differences in the stress response. As a final result, a discrimination accuracy of 100% was obtained to discriminate the three study groups, using the top 20% of features selected by the F-score technique, using the coarse K Nearest Neighbor classifier.Atualmente, o uso de videojogos tem propósitos que vão além do entretenimento e tem vindo a ganhar destaque na área da saúde. Nesse sentido, foi formulada a hipótese de que é possível discriminar sinais biológicos, nomeadamente os sinais eletrocardiográficos e eletroencefalográficos, recolhidos de diferentes participantes estimulados através de três videojogos comerciais diferentes, Tetris, Bejeweled e Energy. Para testar esta hipótese foi desenvolvido um protocolo com o Trier Social Stress Test para induzir e dosear o stress nos sujeitos para níveis semelhantes antes de cada sessão de jogo, de forma a observar os efeitos dos três jogos de teste (3 grupos de estudo) a nível fisiológico. Recolhidos inicialmente a 2000 Hz, os sinais foram reamostrados a 500 Hz e filtrados utilizando um filtro passa-baixo de Butterworth. Após filtragem dos sinais, recolheram-se várias características representativas dos sinais de estudo. Estas características consistiram numa série de métricas não lineares, como o expoente de Lyapunov e a Dimensão de Correlação, métricas de auto similaridade como o exponente de Hurst e a análise de flutuação com trends removidas, dimensões fractais - como as dimensões fractais de Katz e Higuchi - e métricas de caos e atividade dos sinais, como a energia dos sinais, a entropia Logarítmica e a entropia de Shannon, e uma série de métricas espectrais para o sinal EEG, que devem ser capazes de ajudar a identificar qualquer diferença na resposta ao stress. Como resultado final obteve-se uma precisão de discriminação de 100% para discriminar os três grupos de estudo, utilizando as 20% das melhores características selecionadas pela técnica de F-score, recorrendo ao classificador coarse K Nearest Neighbor

    How hand movements and speech tip the balance in cognitive development:A story about children, complexity, coordination, and affordances

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    When someone asks us to explain something, such as how a lever or balance scale works, we spontaneously move our hands and gesture. This is also true for children. Furthermore, children use their hands to discover things and to find out how something works. Previous research has shown that children’s hand movements hereby are ahead of speech, and play a leading role in cognitive development. Explanations for this assumed that cognitive understanding takes place in one’s head, and that hand movements and speech (only) reflect this. However, cognitive understanding arises and consists of the constant interplay between (hand) movements and speech, and someone’s physical and social environment. The physical environment includes task properties, for example, and the social environment includes other people. Therefore, I focused on this constant interplay between hand movements, speech, and the environment, to better understand hand movements’ role in cognitive development. Using science and technology tasks, we found that children’s speech affects hand movements more than the other way around. During difficult tasks the coupling between hand movements and speech becomes even stronger than in easy tasks. Interim changes in task properties differently affect hand movements and speech. Collaborating children coordinate their hand movements and speech, and even their head movements together. The coupling between hand movements and speech is related to age and (school) performance. It is important that teachers attend to children’s hand movements and speech, and arrange their lessons and classrooms such that there is room for both

    Artificial intelligence within the interplay between natural and artificial computation:Advances in data science, trends and applications

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    Artificial intelligence and all its supporting tools, e.g. machine and deep learning in computational intelligence-based systems, are rebuilding our society (economy, education, life-style, etc.) and promising a new era for the social welfare state. In this paper we summarize recent advances in data science and artificial intelligence within the interplay between natural and artificial computation. A review of recent works published in the latter field and the state the art are summarized in a comprehensive and self-contained way to provide a baseline framework for the international community in artificial intelligence. Moreover, this paper aims to provide a complete analysis and some relevant discussions of the current trends and insights within several theoretical and application fields covered in the essay, from theoretical models in artificial intelligence and machine learning to the most prospective applications in robotics, neuroscience, brain computer interfaces, medicine and society, in general.BMS - Pfizer(U01 AG024904). Spanish Ministry of Science, projects: TIN2017-85827-P, RTI2018-098913-B-I00, PSI2015-65848-R, PGC2018-098813-B-C31, PGC2018-098813-B-C32, RTI2018-101114-B-I, TIN2017-90135-R, RTI2018-098743-B-I00 and RTI2018-094645-B-I00; the FPU program (FPU15/06512, FPU17/04154) and Juan de la Cierva (FJCI-2017–33022). Autonomous Government of Andalusia (Spain) projects: UMA18-FEDERJA-084. Consellería de Cultura, Educación e Ordenación Universitaria of Galicia: ED431C2017/12, accreditation 2016–2019, ED431G/08, ED431C2018/29, Comunidad de Madrid, Y2018/EMT-5062 and grant ED431F2018/02. PPMI – a public – private partnership – is funded by The Michael J. Fox Foundation for Parkinson’s Research and funding partners, including Abbott, Biogen Idec, F. Hoffman-La Roche Ltd., GE Healthcare, Genentech and Pfizer Inc

    3D multiple description coding for error resilience over wireless networks

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    Mobile communications has gained a growing interest from both customers and service providers alike in the last 1-2 decades. Visual information is used in many application domains such as remote health care, video –on demand, broadcasting, video surveillance etc. In order to enhance the visual effects of digital video content, the depth perception needs to be provided with the actual visual content. 3D video has earned a significant interest from the research community in recent years, due to the tremendous impact it leaves on viewers and its enhancement of the user’s quality of experience (QoE). In the near future, 3D video is likely to be used in most video applications, as it offers a greater sense of immersion and perceptual experience. When 3D video is compressed and transmitted over error prone channels, the associated packet loss leads to visual quality degradation. When a picture is lost or corrupted so severely that the concealment result is not acceptable, the receiver typically pauses video playback and waits for the next INTRA picture to resume decoding. Error propagation caused by employing predictive coding may degrade the video quality severely. There are several ways used to mitigate the effects of such transmission errors. One widely used technique in International Video Coding Standards is error resilience. The motivation behind this research work is that, existing schemes for 2D colour video compression such as MPEG, JPEG and H.263 cannot be applied to 3D video content. 3D video signals contain depth as well as colour information and are bandwidth demanding, as they require the transmission of multiple high-bandwidth 3D video streams. On the other hand, the capacity of wireless channels is limited and wireless links are prone to various types of errors caused by noise, interference, fading, handoff, error burst and network congestion. Given the maximum bit rate budget to represent the 3D scene, optimal bit-rate allocation between texture and depth information rendering distortion/losses should be minimised. To mitigate the effect of these errors on the perceptual 3D video quality, error resilience video coding needs to be investigated further to offer better quality of experience (QoE) to end users. This research work aims at enhancing the error resilience capability of compressed 3D video, when transmitted over mobile channels, using Multiple Description Coding (MDC) in order to improve better user’s quality of experience (QoE). Furthermore, this thesis examines the sensitivity of the human visual system (HVS) when employed to view 3D video scenes. The approach used in this study is to use subjective testing in order to rate people’s perception of 3D video under error free and error prone conditions through the use of a carefully designed bespoke questionnaire.EThOS - Electronic Theses Online ServicePetroleum Technology Development Fund (PTDF)GBUnited Kingdo

    Google the earth: what's next?

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    Sensing the Earth has proven to be a tremendously valuable tool for understanding the world around us. Over the last half-century, we have built a sophisticated network of satellites, aircraft, and ground-based remote sensing systems to provide raw information from which we derive and improve our knowledge of the Earth and its phenomena. Through remote sensing, our basic scientific knowledge of the Earth and how it functions has expanded rapidly in the last few decades. Applications of this knowledge, from natural hazard prediction to resource management, have already proven their benefit to society many times over. Today maps and satellite imageries have become an integral part of the developmental process and have also triggered new business opportunities. Maps are essential at all stages of infrastructure development, resource planning and the disaster management cycle. Satellite imagery/data can be used for everything from ground truthing and change detection, to more sophisticated analyses, including feature extraction and natural hazard prediction. As imagery has become more accessible and more affordable in recent years, there is also a growing convergence of imagery and geographic information system (GIS) applications. Geospatial scientists and analysts thus, need to be able to easily access imagery and move seamlessly between GIS and image processing applications to derive the most information possible from them. Technologically, the challenge is to design sensors that exhibit high sensitivity to the parameters of interest while minimizing instrument noise and impacts of other natural variables. The scientific challenge is to develop retrieval algorithms that describe the physical measurement process in sufficient detail, yet are simple enough to allow robust inversion of the remotely sensed signals. Considering the exponential growth of data volumes driven by the rapid progress in sensor and computer technologies in recent years, the future of remotely sensed data should ideally be in automated data processing, development of robust and transferable algorithms and processing chains that require little or no human intervention. In meeting the above mentioned challenges, some research works have been done at Universiti Putra Malaysia. These works cover all aspects of the remote sensing process, from instrument design, image processing, image analysis to the retrieval of geophysical parameters and their application in natural resources planning and disaster management. Some of the major research efforts include feature extraction from satellite imagery; spatial decision support system for oil spill detection, monitoring and contingency planning; fish forecasting; UAV-based remote imaging and natural disaster management and early warning systems for floods and landslides. This lecture concludes that through remote sensing, our basic scientific knowledge of the Earth and how it functions have expanded rapidly in the last few decades. Applications of this knowledge, from natural hazard prediction to resource management, have already proven to be beneficial to society many times over. As the demand for even faster, better and more temporally and spatially variable information grows dramatically, this lectures answers the question of what remote sensing will be like in the coming decades and the new capabilities and challenges that will emerg

    Change blindness: eradication of gestalt strategies

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    Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

    Connecting mathematical models for image processing and neural networks

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    This thesis deals with the connections between mathematical models for image processing and deep learning. While data-driven deep learning models such as neural networks are flexible and well performing, they are often used as a black box. This makes it hard to provide theoretical model guarantees and scientific insights. On the other hand, more traditional, model-driven approaches such as diffusion, wavelet shrinkage, and variational models offer a rich set of mathematical foundations. Our goal is to transfer these foundations to neural networks. To this end, we pursue three strategies. First, we design trainable variants of traditional models and reduce their parameter set after training to obtain transparent and adaptive models. Moreover, we investigate the architectural design of numerical solvers for partial differential equations and translate them into building blocks of popular neural network architectures. This yields criteria for stable networks and inspires novel design concepts. Lastly, we present novel hybrid models for inpainting that rely on our theoretical findings. These strategies provide three ways for combining the best of the two worlds of model- and data-driven approaches. Our work contributes to the overarching goal of closing the gap between these worlds that still exists in performance and understanding.Gegenstand dieser Arbeit sind die Zusammenhänge zwischen mathematischen Modellen zur Bildverarbeitung und Deep Learning. Während datengetriebene Modelle des Deep Learning wie z.B. neuronale Netze flexibel sind und gute Ergebnisse liefern, werden sie oft als Black Box eingesetzt. Das macht es schwierig, theoretische Modellgarantien zu liefern und wissenschaftliche Erkenntnisse zu gewinnen. Im Gegensatz dazu bieten traditionellere, modellgetriebene Ansätze wie Diffusion, Wavelet Shrinkage und Variationsansätze eine Fülle von mathematischen Grundlagen. Unser Ziel ist es, diese auf neuronale Netze zu übertragen. Zu diesem Zweck verfolgen wir drei Strategien. Zunächst entwerfen wir trainierbare Varianten von traditionellen Modellen und reduzieren ihren Parametersatz, um transparente und adaptive Modelle zu erhalten. Außerdem untersuchen wir die Architekturen von numerischen Lösern für partielle Differentialgleichungen und übersetzen sie in Bausteine von populären neuronalen Netzwerken. Daraus ergeben sich Kriterien für stabile Netzwerke und neue Designkonzepte. Schließlich präsentieren wir neuartige hybride Modelle für Inpainting, die auf unseren theoretischen Erkenntnissen beruhen. Diese Strategien bieten drei Möglichkeiten, das Beste aus den beiden Welten der modell- und datengetriebenen Ansätzen zu vereinen. Diese Arbeit liefert einen Beitrag zum übergeordneten Ziel, die Lücke zwischen den zwei Welten zu schließen, die noch in Bezug auf Leistung und Modellverständnis besteht.ERC Advanced Grant INCOVI

    A survey of the application of soft computing to investment and financial trading

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