Change detection is an ability that allows intelligent agents to react to unexpected situations. This mechanism is fundamental in providing more autonomy to robots. It has been used in many different fields including quality control and network intrusion. In the visual domain, however, most research has been confined to stationary cameras and only recently have researchers started to shift to mobile cameras. \ We propose a general framework for building internal spatial models of the visual experiences. These models are used to retrieve expectations about visual inputs which can be compared to the actual observation in order to identify the presence of changes. Our framework leverages the tolerance to small view changes of optic flow and color histogram representations and a self-organizing map to build a compact memory of camera observations. The effectiveness of the approach is demonstrated in a walking simulation, where spatial information and color histograms are combined to detect changes in a room. The location signal allows the algorithm to query the self-organizing map for the expected color histogram and compare it to the current input. Any deviations can be considered changes and are then localized on the input image. Furthermore, we show how detecting a vehicle entering or leaving the camera's lane can be reduced to a change detection problem. This simplifies the problem by removing the need to track or even know about other vehicles. Matching Pursuit is used to learn a compact dictionary to describe the observed experiences. Using this approach, changes are detected when the learned dictionary is unable to reconstruct the current input. The human experiments presented in this dissertation support the idea that humans build statistical models that evolve with experience. We provide evidence that not only does this experience improve people's behavior in 3D environments, but also enables them to detect chromatic changes. Mobile cameras are now part of our everyday lives, ranging from built-in laptop cameras to cell phone cameras. The vision of this research is to enable these devices with change detection mechanisms to solve a large class of problems. Beyond presenting a foundation that effectively detects changes in environments, we also show that the algorithms employed are computationally inexpensive. The practicality of this approach is demonstrated by a partial implementation of the algorithm on commodity hardware such as Android mobile devices. / text

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Η παρούσα ειδική ερευνητική εργασία εκπονήθηκε στα πλαίσια του Διατμηματικού Προγράμματος Μεταπτυχιακών Σπουδών στην “Ηλεκτρονική και Επεξεργασία της Πληροφορίας”, στο Τμήμα Φυσικής του Πανεπιστημίου Πατρών. Αντικείμενο της παρούσας εργασίας είναι η “Υλοποίηση σε FPGA του περιγραφέα HOG για ανίχνευση ανθρώπων σε εικόνες και βίντεο”. Το πρώτο κεφάλαιο αποτελεί μια εισαγωγή στις βασικότερες έννοιες που χρησιμοποιούνται στην παρούσα εργασία. Περιγράφεται επίσης η αναπτυξιακή πλακέτα που χρησιμοποιήθηκε καθώς και τα επί μέρους στοιχεία που τη συνθέτουν. Τέλος γίνεται μια συνοπτική αναφορά σε εργασίες με παρόμοιο αντικείμενο, οι οποίες με επηρέασαν στο σχεδιασμό και την υλοποίηση του συστήματός μου. Στο δεύτερο κεφάλαιο αναλύεται ο περιγραφέας Ιστογραμμάτων Προσανατολισμού της Βάθμωσης ή όπως είναι ευρύτερα γνωστός Histograms of Oriented Gradient Descriptor. Παρουσιάζονται τα βήματα όπως περιγράφονται στην εργασία των Dalal&Triggs[4] και οι βέλτιστες τιμές των παραμέτρων του περιγραφέα. Στο τρίτο κεφάλαιο ακολουθώντας τα βήματα του δευτέρου κεφαλαίου, παρουσιάζεται η διαδικασία υλοποίησης του περιγραφέα στο Matlab. Εκτός της υλοποίησης έγινε και μια προεργασία για τη μεταφορά του σε γλώσσα περιγραφής υλικού. Η προεργασία αυτή περιλαμβάνει απλοποιήσεις και τροποποιήσεις με σκοπό να μειωθεί το υπολογιστικό κόστος. Τέλος παρουσιάζονται τα αποτελέσματα δοκιμών της απόδοσης του περιγραφέα για τις διάφορες απλοποιήσεις. Στο τέταρτο κεφάλαιο γίνεται μια μικρή αναφορά στους ταξινομητές. Περιγράφονται οι ταξινομητές που δοκιμάστηκαν στην παρούσα εργασία ως προς συγκεκριμένα χαρακτηριστικά τους καθώς και την υπολογιστική τους πολυπλοκότητα για την συγκεκριμένη εφαρμογή. Το πέμπτο και τελευταίο κεφάλαιο περιλαμβάνει την περιγραφή της υλοποίησης σε VHDL. Αναλύονται τα επί μέρους κυκλώματα και όπου κρίθηκε αναγκαίο χρησιμοποιήθηκαν σχήματα ή πίνακες. Σε κάποιες περιπτώσεις δίνονται και οι κυματομορφές των κυκλωμάτων. / This thesis took place within the frame work of the Interdeparmental Master’s Program in “Electronics and Information Processing”, at the Department of Physics of University of Patras. The objective of this work is the implementation in FPGA of the HOG descriptor for the detection of people, images and videos. The first chapter is an introduction about the basic concepts, which are used across the manuscript. (Additional descriptions concern the development board which was used as well as the individual parts that compose it.) In the end, there is a brief reference to past projects focusing on similar objectives, which influenced the design and the implementation of my system. The second chapter concerns the presentation and discussion of the Histograms of Oriented Gradient descriptor. The steps of the procedure and the best parameter values of the descriptor are presented in a similar way as they are described in the paper of Dalal and Triggs. In the third chapter, following the steps of the previous one, the focus shifts to the descriptor’s implementation procedure in Matlab. Besides the implementation, there is a preparation for the transference of the descriptor in a Hardware Description Language. This preparation includes simplifications and modifications aiming at the reduction of the computational cost. Finally, we see the tests’ results of the descriptor’s performance concerning the various simplifications. The fourth chapter is a partial reference to the classifiers. The description is about the classifiers that were used in the present work with respect to their features and their computational complexity of this particular application. The fifth and final chapter refers to the description of the implementation in VHDL. There is an analysis of the partial circuits and, when necessary, shapes and tables were used. In some cases, the waveforms of the circuits are being presented.

Cette thèse étudie différentes relaxations pour minimiser des fonctionnelles non convexes qui apparaissent en traitement d’images. Des problèmes comme la segmentation d’image peuvent en effet s’écrire comme un problème de minimisation d’une certaine fonctionnelle, le minimiseur représentant la segmentation recherchée. Différentes méthodes ont été proposées pour trouver des minima locaux ou globaux de la fonctionnelle non convexe du modèle de Mumford-Shah constant par morceaux à deux phases. Certaines approches utilisent une relaxation convexe qui permet d’obtenir des minima globaux de la fonctionnelle non convexe. On rappelle et compare certaines de ces méthodes et on propose un nouveau modèle par bande étroite, qui permet d’obtenir des minima locaux tout en utilisant des algorithmes robustes qui proviennent de l’optimisation convexe. Ensuite, on construit une relaxation convexe d’un modèle de segmentation à deux phases qui repose sur la comparaison entre deux histogrammes donnés et les histogrammes estimés globalement sur les deux régions de la segmentation. Des relaxations pour des problèmes multi-étiquettes à plusieurs dimensions comme le flot optique sont également étudiées. On propose une relaxation convexe avec un algorithme itératif qui ne comprend que des projections qui se calculent exactement, ainsi qu’un nouvel algorithme pour une relaxation convexe sur chaque variable mais non convexe globalement. On étudie la manière d’estimer une solution du problème non convexe original à partir d’une solution d’un problème relaxé en comparant des méthodes existantes avec des nouvelles / In this thesis we study different relaxations of non-convex functionals that can be found in image processing. Some problems, such as image segmentation, can indeed be written as the minimization of a functional. The minimizer of the functional represents the segmentation. Different methods have been proposed in order to find local or global minima of the non-convex functional of the two-phase piecewise constant Mumford-Shah model. With a convex relaxation of this model we can find a global minimum of the nonconvex functional. We present and compare some of these methods and we propose a new model with a narrow band. This model finds local minima while using robust convex optimization algorithms. Then a convex relaxation of a two-phase segmentation model is built that compares two given histograms with those of the two segmented regions. We also study some relaxations of high-dimension multi-label problems such as optical flow computation. A convex relaxation with a new algorithm is proposed. The algorithm is iterative with exact projections. A new algorithm is given for a relaxationthat is convex in each variable but that is not convex globally. We study the problem of constructing a solution of the original non-convex problem with a solution of the relaxed problem. We compare existing methods with new ones.

In applied research, a lack of understanding of corner stall, i.e. the three-dimensional (3D) separation in the juncture of the endwall and blade corner region, which has limited the efficiency and the stability of compressors. Both Reynolds-averaged Navier-Stokes (RANS) and large eddy simulation (LES) still need to be calibrated for turbomachinery applications. In the fundamental research of the turbulent boundary layer (TBL), there are a lot of findings of the effects of curvature and pressure gradients, which also play an important role in physics of corner stall. The purpose of this thesis is (i) to carry out an experiment in a cascade, (ii) to gain a database that could be used to calibrate both RANS and LES, and (iii) to give some basic explanations of corner stall through investigating the TBL on the suction side at the mid-span which is more complex than those in the basic investigations but simpler than those in a real engine. A detailed and accurate experiment of 3D flow field through a linear compressor cascade has been set up. Experimental data were acquired for a Reynolds number of 3.82×10 ^5 based on blade chord and inlet flow conditions. Measurements have been achieved by hot-wire anemometry, pressure taps on blade and endwall, five-hole pressure probe, oil visualization, 2D particle image velocimetry (PIV),and two-component laser Doppler anemometry (LDA). An original and complete database was thus obtained. The TBL on the suction side at mid-span was investigated. The wall-normal negative pressure gradient restrains the separation, on the contrary to its influence in the corner stall. The streamwise adverse pressure gradient can be responsible for the development of Reynolds stresses. The remarkable phenomenon at measurement stations near the trailing edge of blade is that an inflection point occurs in each profile of the mean streamwise velocity. At this inflection point, the magnitudes of the Reynolds stresses reach their maximum values, and the direction of energy diffusion also changes. The velocity field in the corner stall was presented. Bimodal histograms of velocity exist in the experiment. The bimodal points mainly appear in the region around the mean interface of separated flow and non-separated flow. At a bimodal point the local two velocity components are non-independent from each other, due to the aperiodic interplay of two basic modes in the flow field. Two modes were proposed to interpret the physics of bimodal behaviour.

[pt] Esta tese apresenta e examina contribuições inovadoras no front-end dos sistemas de reconhecimento automático de voz (RAV) para o realce e reconhecimento de voz em ambientes adversos. A primeira proposta consiste em aplicar um filtro de mediana sobre a função de distribuição de probabilidade de cada coeficiente cepstral antes de utilizar uma transformação para um domínio invariante às distorções, com o objetivo de adaptar a voz ruidosa ao ambiente limpo de referência através da modificação de histogramas. Fundamentadas nos resultados de estudos psicofísicos do sistema auditivo humano, que utiliza como princípio o fato de que o som que atinge o ouvido é sujeito a um processo chamado Análise de Cena Auditiva (ASA), o qual examina como o sistema auditivo separa as fontes de som que compõem a entrada acústica, três novas abordagens aplicadas independentemente foram propostas para realce e reconhecimento de voz. A primeira aplica a estimativa de uma nova máscara no domínio espectral usando o conceito da transformada de Fourier de tempo curto (STFT). A máscara proposta aplica a técnica Local Binary Pattern (LBP) à relação sinal ruído (SNR) de cada unidade de tempo-frequência (T-F) para estimar uma máscara de vizinhança ideal (INM). Continuando com essa abordagem, propõe-se em seguida nesta tese o mascaramento usando as transformadas wavelet com base nos LBP para realçar os espectros temporais dos coeficientes wavelet nas altas frequências. Finalmente, é proposto um novo método de estimação da máscara INM, utilizando um algoritmo de aprendizagem supervisionado das Deep Neural Networks (DNN) com o objetivo de realizar a classificação de unidades T-F obtidas da saída dos bancos de filtros pertencentes a uma mesma fonte de som (ou predominantemente voz ou predominantemente ruído). O desempenho é comparado com as técnicas de máscara tradicionais IBM e IRM, tanto em termos de qualidade objetiva da voz, como através de taxas de erro de palavra. Os resultados das técnicas propostas evidenciam as melhoras obtidas em ambientes ruidosos, com diferenças significativamente superiores às abordagens convencionais. / [en] This thesis presents and examines innovative contributions in frontend of the automatic speech recognition systems (ASR) for enhancement and speech recognition in adverse environments. The first proposal applies a median filter on the probability distribution function of each cepstral coefficient before using a transformation to a distortion-invariant domain, to adapt the corrupted voice to the clean reference environment by modifying histograms. Based on the results of psychophysical studies of the human auditory system, which uses as a principle the fact that sound reaching the ear is subjected to a process called Auditory Scene Analysis (ASA), which examines how the auditory system separates the sound sources that make up the acoustic input, three new approaches independently applied were proposed for enhancement and speech recognition. The first applies the estimation of a new mask in the spectral domain using the short-time Fourier Transform (STFT) concept. The proposed mask applies the Local Binary Pattern (LBP) technique to the Signal-to-Noise Ratio (SNR) of each time-frequency unit (T-F) to estimate an Ideal Neighborhood Mask (INM). Continuing with this approach, the masking using LBP-based wavelet transforms to highlight the temporal spectra of wavelet coefficients at high frequencies is proposed in this thesis. Finally, a new method of estimation of the INM mask is proposed, using a supervised learning algorithm of Deep Neural Network (DNN) to classify the T-F units obtained from the output of the filter banks belonging to a same source of sound (or predominantly voice or predominantly noise). The performance is compared with traditional IBM and IRM mask techniques, both regarding objective voice quality and through word error rates. The results of the proposed methods show the improvements obtained in noisy environments, with differences significantly superior to the conventional approaches.

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No. of bitstreams: 2 Tese - Thiago Borges de Oliveira - 2017.pdf: 1684209 bytes, checksum: f64b32084ca6b13a58109e4d2cffe541 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-11-29 / Multiway spatial join is an important type of query in spatial data processing, and its efficient execution is a requirement to move spatial data analysis to scalable platforms as has already happened with relational and unstructured data. In this thesis, we provide a set of comprehensive models and methods to efficiently execute multiway spatial join queries in distributed systems. We introduce a cost-based optimizer that is able to select a good execution plan for processing such queries in distributed systems taking into account: the partitioning of data based on the spatial attributes of datasets; the intra-operator level of parallelism, which enables high scalability; and the economy of cluster resources by appropriately scheduling the queries before execution. We propose a cost model based on relevant metadata about the spatial datasets and the data distribution, which identifies the pattern of costs incurred when processing a query in this environment. We formalized the distributed multiway spatial join plan scheduling problem as a bi-objective linear integer model, considering the minimization of both the makespan and the communication cost as objectives. Three methods are proposed to compute schedules based on this model that significantly reduce the resource consumption required to process a query. Although targeting multiway spatial join query scheduling, these methods can be applied to other kinds of problems in distributed systems, notably problems that require both the alignment of data partitions and the assignment of jobs to machines. Additionally, we propose a method to control the usage of resources and increase system throughput in the presence of constraints on the network or processing capacity. The proposed cost-based optimizer was able to select good execution plans for all queries in our experiments, using public datasets with a significant range of sizes and complex spatial objects. We also present an execution engine that is capable of performing the queries with near-linear scalability with respect to execution time. / A multi-junção espacial é um tipo importante de consulta usada no processamento de dados espaciais e sua execução eficiente é um requisito para mover a análise de dados espaciais para plataformas escaláveis, assim como aconteceu com dados relacionais e não estruturados. Nesta tese, propomos um conjunto de modelos e métodos para executar eficientemente consultas de multi-junção espacial em sistemas distribuídos. Apresentamos um otimizador baseado em custos que seleciona um bom plano de execução levando em consideração: o particionamento de dados com base nos atributos espaciais dos datasets; o nível de paralelismo intra-operador que proporciona alta escalabilidade; e o escalonamento das consultas antes da execução que resulta em economia de recursos computacionais. Propomos um modelo de custo baseado em metadados dos datasets e da distribuição de dados, que identifica o padrão de custos incorridos no processamento de uma consulta neste ambiente. Formalizamos o problema de escalonamento de planos de execução da multi-junção espacial distribuída como um modelo linear inteiro bi-objetivo, que minimiza tanto o custo de processamento quanto o custo de comunicação. Propomos três métodos para gerar escalonamentos a partir deste modelo, os quais reduzem significativamente o consumo de recursos no processamento das consultas. Embora projetados para o escalonamento da multi-junção espacial, esses métodos podem também ser aplicados a outros tipos de problemas em sistemas distribuídos, que necessitam do alinhamento de partições de dados e da distribuição de tarefas a máquinas de forma balanceada. Além disso, propomos um método para controlar o uso de recursos e aumentar a vazão do sistema na presença de restrições nas capacidades da rede ou de processamento. O otimizador proposto foi capaz de selecionar bons planos de execução para todas as consultas em nossos experimentos, as quais usaram datasets públicos com uma variedade significativa de tamanhos e de objetos espaciais complexos. Apresentamos também uma máquina de execução, capaz de executar as consultas com escalabilidade próxima de linear em relação ao tempo de execução.

Dans le domaine de la recherche appliquée, les turbomachinistes sont confrontés à un manque de compréhension de la physique du décollement de coin. Ce décollement tridimensionnel (3D) à la jonction de l’extrados des aubages et du moyeu limite l’efficacité et la stabilité des compresseurs. Les simulations numériques utilisant les deux types de modélisations, « Reynolds-Averaged-Navier-Stokes » (RANS) et « Large Eddy Simulation » (LES), doivent encore être étalonnées pour des applications turbomachines. Dans la recherche fondamentale concernant la couche limite turbulente (TBL), il existe beaucoup d’études sur les effets de courbure et de gradients de pression qui jouent également un rôle important dans la physique du décollement de coin. Le but de cette thèse est de réaliser une expérience dans une grille d’aubes de compresseur pour acquérir une base de données qui pourrait être utilisée non seulement pour calibrer à la fois les approches RANS et LES, mais aussi pour donner quelques explications fondamentales sur le décollement de coin. Cette expérience permet aussi une étude de la TBL se développant sur l’extrados à mi-envergure des aubages, qui est plus complexe que les TBL rencontrées dans des configurations plus fondamentales, mais plus simples que celles existant d’un turboréacteur. Une expérience précise et détaillée de l’écoulement 3D au passage d’une grille d’aubes de compresseur a été mis en place. Les mesures ont été réalisées pour un nombre de Reynolds basé sur les conditions d’entrée et la corde de l’aubage de 3,82×105. Des mesures ont été réalisées par anémométrie à fil chaud, par des prises de pression sur la paroi latérale et sur l’aubage, par une sonde de pression à cinq trous, par de la visualisation d’huile, par la Vélocimétrie par Images de Particules (PIV) 2D, ainsi que par Anémométrie Laser Doppler (LDA) à deux composants. Une base de données originale et complète a ainsi été obtenue. Concernant l’étude de la TBL sur l’extrados à mi-envergure , le gradient négatif de pression normal à la paroi retarde le décollement, ce qui est paradoxal avec son influence sur le décollement de coin tel que présentée dans la littérature. Le gradient de pression adverse dans la direction de l’écoulement est responsable de l’accroissement des tensions de Reynolds. Un phénomène remarquable proche du bord de fuite de l’aubage est qu’il existe un point d’inflexion dans le profil de la vitesse moyenne de l’écoulement. A ce point d’inflexion, les grandeurs des tensions de Reynolds atteignent leurs valeurs maximales et la direction de diffusion de l’énergie est inversée. Le champ de vitesse dans le décollement de coin a été présenté. L’expérience met en évidence l’existence d’histogrammes bimodaux de vitesse. Les points de mesures faisant apparaitre ce caractère bimodal sont essentiellement localisés dans la région de l’interface du décollement de l’écoulement moyenné en temps. Deux modes ont été proposés pour interpréter la physique du comportement bimodal. Pour un point bimodal, les deux composantes de vitesse sont localement non-indépendantes, en raison de l’interaction apériodique de ces deux modes. / In applied research, a lack of understanding of corner stall, i.e. the three-dimensional (3D) separation in the juncture of the endwall and blade corner region, which has limited the efficiency and the stability of compressors. Both Reynolds-averaged Navier-Stokes (RANS) and large eddy simulation (LES) still need to be calibrated for turbomachinery applications. In the fundamental research of the turbulent boundary layer (TBL), there are a lot of findings of the effects of curvature and pressure gradients, which also play an important role in physics of corner stall. The purpose of this thesis is (i) to carry out an experiment in a cascade, (ii) to gain a database that could be used to calibrate both RANS and LES, and (iii) to give some basic explanations of corner stall through investigating the TBL on the suction side at the mid-span which is more complex than those in the basic investigations but simpler than those in a real engine. A detailed and accurate experiment of 3D flow field through a linear compressor cascade has been set up. Experimental data were acquired for a Reynolds number of 3.82×10 ^5 based on blade chord and inlet flow conditions. Measurements have been achieved by hot-wire anemometry, pressure taps on blade and endwall, five-hole pressure probe, oil visualization, 2D particle image velocimetry (PIV),and two-component laser Doppler anemometry (LDA). An original and complete database was thus obtained. The TBL on the suction side at mid-span was investigated. The wall-normal negative pressure gradient restrains the separation, on the contrary to its influence in the corner stall. The streamwise adverse pressure gradient can be responsible for the development of Reynolds stresses. The remarkable phenomenon at measurement stations near the trailing edge of blade is that an inflection point occurs in each profile of the mean streamwise velocity. At this inflection point, the magnitudes of the Reynolds stresses reach their maximum values, and the direction of energy diffusion also changes. The velocity field in the corner stall was presented. Bimodal histograms of velocity exist in the experiment. The bimodal points mainly appear in the region around the mean interface of separated flow and non-separated flow. At a bimodal point the local two velocity components are non-independent from each other, due to the aperiodic interplay of two basic modes in the flow field. Two modes were proposed to interpret the physics of bimodal behaviour.

This thesis aims to evaluate a new manufacturing process by using statistical methods SPC. In the theoretical part provides the basic methods and rules applied in the assessment of control charts. The next part evaluates the current state of the company Hanhart Morkovice s.r.o. analysis and production of coils. The analytical part deals with control charts for reference and quality characters using statistical software process capability indexes and control charts. Based on information from the analytical part, conclusions are drawn and designed for long-term steps using established methods of SPC for quality characters.

This diploma thesis deals with a Six Sigma method, about especially analysis defects of forms for tire production company Barum Continental. In the first, theoretic part, there is the Six Sigma method, improvement method and implementation into practice defined, and at last I attended to the tools of Six Sigma method, e. g. Control Charts, Regression analysis, Pareto analysis. In the second, practical part, there is the industrial process analyzed. Then I was introduced Barum Continental spol. s.r.o. concern, which data extended. Up to data processing I was used tools of Six Sigma method and also histogram.