48 resultados para coded camera array

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La astronomía de rayos γ estudia las partículas más energéticas que llegan a la Tierra desde el espacio. Estos rayos γ no se generan mediante procesos térmicos en simples estrellas, sino mediante mecanismos de aceleración de partículas en objetos celestes como núcleos de galaxias activos, púlsares, supernovas, o posibles procesos de aniquilación de materia oscura. Los rayos γ procedentes de estos objetos y sus características proporcionan una valiosa información con la que los científicos tratan de comprender los procesos físicos que ocurren en ellos y desarrollar modelos teóricos que describan su funcionamiento con fidelidad. El problema de observar rayos γ es que son absorbidos por las capas altas de la atmósfera y no llegan a la superficie (de lo contrario, la Tierra será inhabitable). De este modo, sólo hay dos formas de observar rayos γ embarcar detectores en satélites, u observar los efectos secundarios que los rayos γ producen en la atmósfera. Cuando un rayo γ llega a la atmósfera, interacciona con las partículas del aire y genera un par electrón - positrón, con mucha energía. Estas partículas secundarias generan a su vez más partículas secundarias cada vez menos energéticas. Estas partículas, mientras aún tienen energía suficiente para viajar más rápido que la velocidad de la luz en el aire, producen una radiación luminosa azulada conocida como radiación Cherenkov durante unos pocos nanosegundos. Desde la superficie de la Tierra, algunos telescopios especiales, conocidos como telescopios Cherenkov o IACTs (Imaging Atmospheric Cherenkov Telescopes), son capaces de detectar la radiación Cherenkov e incluso de tomar imágenes de la forma de la cascada Cherenkov. A partir de estas imágenes es posible conocer las principales características del rayo γ original, y con suficientes rayos se pueden deducir características importantes del objeto que los emitió, a cientos de años luz de distancia. Sin embargo, detectar cascadas Cherenkov procedentes de rayos γ no es nada fácil. Las cascadas generadas por fotones γ de bajas energías emiten pocos fotones, y durante pocos nanosegundos, y las correspondientes a rayos γ de alta energía, si bien producen más electrones y duran más, son más improbables conforme mayor es su energía. Esto produce dos líneas de desarrollo de telescopios Cherenkov: Para observar cascadas de bajas energías son necesarios grandes reflectores que recuperen muchos fotones de los pocos que tienen estas cascadas. Por el contrario, las cascadas de altas energías se pueden detectar con telescopios pequeños, pero conviene cubrir con ellos una superficie grande en el suelo para aumentar el número de eventos detectados. Con el objetivo de mejorar la sensibilidad de los telescopios Cherenkov actuales, en el rango de energía alto (> 10 TeV), medio (100 GeV - 10 TeV) y bajo (10 GeV - 100 GeV), nació el proyecto CTA (Cherenkov Telescope Array). Este proyecto en el que participan más de 27 países, pretende construir un observatorio en cada hemisferio, cada uno de los cuales contará con 4 telescopios grandes (LSTs), unos 30 medianos (MSTs) y hasta 70 pequeños (SSTs). Con un array así, se conseguirán dos objetivos. En primer lugar, al aumentar drásticamente el área de colección respecto a los IACTs actuales, se detectarán más rayos γ en todos los rangos de energía. En segundo lugar, cuando una misma cascada Cherenkov es observada por varios telescopios a la vez, es posible analizarla con mucha más precisión gracias a las técnicas estereoscópicas. La presente tesis recoge varios desarrollos técnicos realizados como aportación a los telescopios medianos y grandes de CTA, concretamente al sistema de trigger. Al ser las cascadas Cherenkov tan breves, los sistemas que digitalizan y leen los datos de cada píxel tienen que funcionar a frecuencias muy altas (≈1 GHz), lo que hace inviable que funcionen de forma continua, ya que la cantidad de datos guardada será inmanejable. En su lugar, las señales analógicas se muestrean, guardando las muestras analógicas en un buffer circular de unos pocos µs. Mientras las señales se mantienen en el buffer, el sistema de trigger hace un análisis rápido de las señales recibidas, y decide si la imagen que hay en el buér corresponde a una cascada Cherenkov y merece ser guardada, o por el contrario puede ignorarse permitiendo que el buffer se sobreescriba. La decisión de si la imagen merece ser guardada o no, se basa en que las cascadas Cherenkov producen detecciones de fotones en píxeles cercanos y en tiempos muy próximos, a diferencia de los fotones de NSB (night sky background), que llegan aleatoriamente. Para detectar cascadas grandes es suficiente con comprobar que más de un cierto número de píxeles en una región hayan detectado más de un cierto número de fotones en una ventana de tiempo de algunos nanosegundos. Sin embargo, para detectar cascadas pequeñas es más conveniente tener en cuenta cuántos fotones han sido detectados en cada píxel (técnica conocida como sumtrigger). El sistema de trigger desarrollado en esta tesis pretende optimizar la sensibilidad a bajas energías, por lo que suma analógicamente las señales recibidas en cada píxel en una región de trigger y compara el resultado con un umbral directamente expresable en fotones detectados (fotoelectrones). El sistema diseñado permite utilizar regiones de trigger de tamaño seleccionable entre 14, 21 o 28 píxeles (2, 3, o 4 clusters de 7 píxeles cada uno), y con un alto grado de solapamiento entre ellas. De este modo, cualquier exceso de luz en una región compacta de 14, 21 o 28 píxeles es detectado y genera un pulso de trigger. En la versión más básica del sistema de trigger, este pulso se distribuye por toda la cámara de forma que todos los clusters sean leídos al mismo tiempo, independientemente de su posición en la cámara, a través de un delicado sistema de distribución. De este modo, el sistema de trigger guarda una imagen completa de la cámara cada vez que se supera el número de fotones establecido como umbral en una región de trigger. Sin embargo, esta forma de operar tiene dos inconvenientes principales. En primer lugar, la cascada casi siempre ocupa sólo una pequeña zona de la cámara, por lo que se guardan muchos píxeles sin información alguna. Cuando se tienen muchos telescopios como será el caso de CTA, la cantidad de información inútil almacenada por este motivo puede ser muy considerable. Por otro lado, cada trigger supone guardar unos pocos nanosegundos alrededor del instante de disparo. Sin embargo, en el caso de cascadas grandes la duración de las mismas puede ser bastante mayor, perdiéndose parte de la información debido al truncamiento temporal. Para resolver ambos problemas se ha propuesto un esquema de trigger y lectura basado en dos umbrales. El umbral alto decide si hay un evento en la cámara y, en caso positivo, sólo las regiones de trigger que superan el nivel bajo son leídas, durante un tiempo más largo. De este modo se evita guardar información de píxeles vacíos y las imágenes fijas de las cascadas se pueden convertir en pequeños \vídeos" que representen el desarrollo temporal de la cascada. Este nuevo esquema recibe el nombre de COLIBRI (Concept for an Optimized Local Image Building and Readout Infrastructure), y se ha descrito detalladamente en el capítulo 5. Un problema importante que afecta a los esquemas de sumtrigger como el que se presenta en esta tesis es que para sumar adecuadamente las señales provenientes de cada píxel, estas deben tardar lo mismo en llegar al sumador. Los fotomultiplicadores utilizados en cada píxel introducen diferentes retardos que deben compensarse para realizar las sumas adecuadamente. El efecto de estos retardos ha sido estudiado, y se ha desarrollado un sistema para compensarlos. Por último, el siguiente nivel de los sistemas de trigger para distinguir efectivamente las cascadas Cherenkov del NSB consiste en buscar triggers simultáneos (o en tiempos muy próximos) en telescopios vecinos. Con esta función, junto con otras de interfaz entre sistemas, se ha desarrollado un sistema denominado Trigger Interface Board (TIB). Este sistema consta de un módulo que irá montado en la cámara de cada LST o MST, y que estará conectado mediante fibras ópticas a los telescopios vecinos. Cuando un telescopio tiene un trigger local, este se envía a todos los vecinos conectados y viceversa, de modo que cada telescopio sabe si sus vecinos han dado trigger. Una vez compensadas las diferencias de retardo debidas a la propagación en las fibras ópticas y de los propios fotones Cherenkov en el aire dependiendo de la dirección de apuntamiento, se buscan coincidencias, y en el caso de que la condición de trigger se cumpla, se lee la cámara en cuestión, de forma sincronizada con el trigger local. Aunque todo el sistema de trigger es fruto de la colaboración entre varios grupos, fundamentalmente IFAE, CIEMAT, ICC-UB y UCM en España, con la ayuda de grupos franceses y japoneses, el núcleo de esta tesis son el Level 1 y la Trigger Interface Board, que son los dos sistemas en los que que el autor ha sido el ingeniero principal. Por este motivo, en la presente tesis se ha incluido abundante información técnica relativa a estos sistemas. Existen actualmente importantes líneas de desarrollo futuras relativas tanto al trigger de la cámara (implementación en ASICs), como al trigger entre telescopios (trigger topológico), que darán lugar a interesantes mejoras sobre los diseños actuales durante los próximos años, y que con suerte serán de provecho para toda la comunidad científica participante en CTA. ABSTRACT -ray astronomy studies the most energetic particles arriving to the Earth from outer space. This -rays are not generated by thermal processes in mere stars, but by means of particle acceleration mechanisms in astronomical objects such as active galactic nuclei, pulsars, supernovas or as a result of dark matter annihilation processes. The γ rays coming from these objects and their characteristics provide with valuable information to the scientist which try to understand the underlying physical fundamentals of these objects, as well as to develop theoretical models able to describe them accurately. The problem when observing rays is that they are absorbed in the highest layers of the atmosphere, so they don't reach the Earth surface (otherwise the planet would be uninhabitable). Therefore, there are only two possible ways to observe γ rays: by using detectors on-board of satellites, or by observing their secondary effects in the atmosphere. When a γ ray reaches the atmosphere, it interacts with the particles in the air generating a highly energetic electron-positron pair. These secondary particles generate in turn more particles, with less energy each time. While these particles are still energetic enough to travel faster than the speed of light in the air, they produce a bluish radiation known as Cherenkov light during a few nanoseconds. From the Earth surface, some special telescopes known as Cherenkov telescopes or IACTs (Imaging Atmospheric Cherenkov Telescopes), are able to detect the Cherenkov light and even to take images of the Cherenkov showers. From these images it is possible to know the main parameters of the original -ray, and with some -rays it is possible to deduce important characteristics of the emitting object, hundreds of light-years away. However, detecting Cherenkov showers generated by γ rays is not a simple task. The showers generated by low energy -rays contain few photons and last few nanoseconds, while the ones corresponding to high energy -rays, having more photons and lasting more time, are much more unlikely. This results in two clearly differentiated development lines for IACTs: In order to detect low energy showers, big reflectors are required to collect as much photons as possible from the few ones that these showers have. On the contrary, small telescopes are able to detect high energy showers, but a large area in the ground should be covered to increase the number of detected events. With the aim to improve the sensitivity of current Cherenkov showers in the high (> 10 TeV), medium (100 GeV - 10 TeV) and low (10 GeV - 100 GeV) energy ranges, the CTA (Cherenkov Telescope Array) project was created. This project, with more than 27 participating countries, intends to build an observatory in each hemisphere, each one equipped with 4 large size telescopes (LSTs), around 30 middle size telescopes (MSTs) and up to 70 small size telescopes (SSTs). With such an array, two targets would be achieved. First, the drastic increment in the collection area with respect to current IACTs will lead to detect more -rays in all the energy ranges. Secondly, when a Cherenkov shower is observed by several telescopes at the same time, it is possible to analyze it much more accurately thanks to the stereoscopic techniques. The present thesis gathers several technical developments for the trigger system of the medium and large size telescopes of CTA. As the Cherenkov showers are so short, the digitization and readout systems corresponding to each pixel must work at very high frequencies (_ 1 GHz). This makes unfeasible to read data continuously, because the amount of data would be unmanageable. Instead, the analog signals are sampled, storing the analog samples in a temporal ring buffer able to store up to a few _s. While the signals remain in the buffer, the trigger system performs a fast analysis of the signals and decides if the image in the buffer corresponds to a Cherenkov shower and deserves to be stored, or on the contrary it can be ignored allowing the buffer to be overwritten. The decision of saving the image or not, is based on the fact that Cherenkov showers produce photon detections in close pixels during near times, in contrast to the random arrival of the NSB phtotons. Checking if more than a certain number of pixels in a trigger region have detected more than a certain number of photons during a certain time window is enough to detect large showers. However, taking also into account how many photons have been detected in each pixel (sumtrigger technique) is more convenient to optimize the sensitivity to low energy showers. The developed trigger system presented in this thesis intends to optimize the sensitivity to low energy showers, so it performs the analog addition of the signals received in each pixel in the trigger region and compares the sum with a threshold which can be directly expressed as a number of detected photons (photoelectrons). The trigger system allows to select trigger regions of 14, 21, or 28 pixels (2, 3 or 4 clusters with 7 pixels each), and with extensive overlapping. In this way, every light increment inside a compact region of 14, 21 or 28 pixels is detected, and a trigger pulse is generated. In the most basic version of the trigger system, this pulse is just distributed throughout the camera in such a way that all the clusters are read at the same time, independently from their position in the camera, by means of a complex distribution system. Thus, the readout saves a complete camera image whenever the number of photoelectrons set as threshold is exceeded in a trigger region. However, this way of operating has two important drawbacks. First, the shower usually covers only a little part of the camera, so many pixels without relevant information are stored. When there are many telescopes as will be the case of CTA, the amount of useless stored information can be very high. On the other hand, with every trigger only some nanoseconds of information around the trigger time are stored. In the case of large showers, the duration of the shower can be quite larger, loosing information due to the temporal cut. With the aim to solve both limitations, a trigger and readout scheme based on two thresholds has been proposed. The high threshold decides if there is a relevant event in the camera, and in the positive case, only the trigger regions exceeding the low threshold are read, during a longer time. In this way, the information from empty pixels is not stored and the fixed images of the showers become to little \`videos" containing the temporal development of the shower. This new scheme is named COLIBRI (Concept for an Optimized Local Image Building and Readout Infrastructure), and it has been described in depth in chapter 5. An important problem affecting sumtrigger schemes like the one presented in this thesis is that in order to add the signals from each pixel properly, they must arrive at the same time. The photomultipliers used in each pixel introduce different delays which must be compensated to perform the additions properly. The effect of these delays has been analyzed, and a delay compensation system has been developed. The next trigger level consists of looking for simultaneous (or very near in time) triggers in neighbour telescopes. These function, together with others relating to interfacing different systems, have been developed in a system named Trigger Interface Board (TIB). This system is comprised of one module which will be placed inside the LSTs and MSTs cameras, and which will be connected to the neighbour telescopes through optical fibers. When a telescope receives a local trigger, it is resent to all the connected neighbours and vice-versa, so every telescope knows if its neighbours have been triggered. Once compensated the delay differences due to propagation in the optical fibers and in the air depending on the pointing direction, the TIB looks for coincidences, and in the case that the trigger condition is accomplished, the camera is read a fixed time after the local trigger arrived. Despite all the trigger system is the result of the cooperation of several groups, specially IFAE, Ciemat, ICC-UB and UCM in Spain, with some help from french and japanese groups, the Level 1 and the Trigger Interface Board constitute the core of this thesis, as they have been the two systems designed by the author of the thesis. For this reason, a large amount of technical information about these systems has been included. There are important future development lines regarding both the camera trigger (implementation in ASICS) and the stereo trigger (topological trigger), which will produce interesting improvements for the current designs during the following years, being useful for all the scientific community participating in CTA.

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This study presents a robust method for ground plane detection in vision-based systems with a non-stationary camera. The proposed method is based on the reliable estimation of the homography between ground planes in successive images. This homography is computed using a feature matching approach, which in contrast to classical approaches to on-board motion estimation does not require explicit ego-motion calculation. As opposed to it, a novel homography calculation method based on a linear estimation framework is presented. This framework provides predictions of the ground plane transformation matrix that are dynamically updated with new measurements. The method is specially suited for challenging environments, in particular traffic scenarios, in which the information is scarce and the homography computed from the images is usually inaccurate or erroneous. The proposed estimation framework is able to remove erroneous measurements and to correct those that are inaccurate, hence producing a reliable homography estimate at each instant. It is based on the evaluation of the difference between the predicted and the observed transformations, measured according to the spectral norm of the associated matrix of differences. Moreover, an example is provided on how to use the information extracted from ground plane estimation to achieve object detection and tracking. The method has been successfully demonstrated for the detection of moving vehicles in traffic environments.

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Below are the results of the survey of the Iberian lynx obtained with camera-trapping between 2000 and 2007 in Sierra Morena. Two very important aspects of camera-trapping concerning its efficiency are also analyzed. The first is the evolution along years according to the camera-trapping type used of two efficiency indicators. The results obtained demonstrate that the most efficient lure is rabbit, though it is the less proven (92 trap-nights), followed by camera-trapping in the most frequent marking places (latrines). And, we propose as a novel the concept of use area as a spatial reference unit for the camera-trapping monitoring of non radio-marked animals is proposed, and its validity discussed.

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En esta tesis se aborda la detección y el seguimiento automático de vehículos mediante técnicas de visión artificial con una cámara monocular embarcada. Este problema ha suscitado un gran interés por parte de la industria automovilística y de la comunidad científica ya que supone el primer paso en aras de la ayuda a la conducción, la prevención de accidentes y, en última instancia, la conducción automática. A pesar de que se le ha dedicado mucho esfuerzo en los últimos años, de momento no se ha encontrado ninguna solución completamente satisfactoria y por lo tanto continúa siendo un tema de investigación abierto. Los principales problemas que plantean la detección y seguimiento mediante visión artificial son la gran variabilidad entre vehículos, un fondo que cambia dinámicamente debido al movimiento de la cámara, y la necesidad de operar en tiempo real. En este contexto, esta tesis propone un marco unificado para la detección y seguimiento de vehículos que afronta los problemas descritos mediante un enfoque estadístico. El marco se compone de tres grandes bloques, i.e., generación de hipótesis, verificación de hipótesis, y seguimiento de vehículos, que se llevan a cabo de manera secuencial. No obstante, se potencia el intercambio de información entre los diferentes bloques con objeto de obtener el máximo grado posible de adaptación a cambios en el entorno y de reducir el coste computacional. Para abordar la primera tarea de generación de hipótesis, se proponen dos métodos complementarios basados respectivamente en el análisis de la apariencia y la geometría de la escena. Para ello resulta especialmente interesante el uso de un dominio transformado en el que se elimina la perspectiva de la imagen original, puesto que este dominio permite una búsqueda rápida dentro de la imagen y por tanto una generación eficiente de hipótesis de localización de los vehículos. Los candidatos finales se obtienen por medio de un marco colaborativo entre el dominio original y el dominio transformado. Para la verificación de hipótesis se adopta un método de aprendizaje supervisado. Así, se evalúan algunos de los métodos de extracción de características más populares y se proponen nuevos descriptores con arreglo al conocimiento de la apariencia de los vehículos. Para evaluar la efectividad en la tarea de clasificación de estos descriptores, y dado que no existen bases de datos públicas que se adapten al problema descrito, se ha generado una nueva base de datos sobre la que se han realizado pruebas masivas. Finalmente, se presenta una metodología para la fusión de los diferentes clasificadores y se plantea una discusión sobre las combinaciones que ofrecen los mejores resultados. El núcleo del marco propuesto está constituido por un método Bayesiano de seguimiento basado en filtros de partículas. Se plantean contribuciones en los tres elementos fundamentales de estos filtros: el algoritmo de inferencia, el modelo dinámico y el modelo de observación. En concreto, se propone el uso de un método de muestreo basado en MCMC que evita el elevado coste computacional de los filtros de partículas tradicionales y por consiguiente permite que el modelado conjunto de múltiples vehículos sea computacionalmente viable. Por otra parte, el dominio transformado mencionado anteriormente permite la definición de un modelo dinámico de velocidad constante ya que se preserva el movimiento suave de los vehículos en autopistas. Por último, se propone un modelo de observación que integra diferentes características. En particular, además de la apariencia de los vehículos, el modelo tiene en cuenta también toda la información recibida de los bloques de procesamiento previos. El método propuesto se ejecuta en tiempo real en un ordenador de propósito general y da unos resultados sobresalientes en comparación con los métodos tradicionales. ABSTRACT This thesis addresses on-road vehicle detection and tracking with a monocular vision system. This problem has attracted the attention of the automotive industry and the research community as it is the first step for driver assistance and collision avoidance systems and for eventual autonomous driving. Although many effort has been devoted to address it in recent years, no satisfactory solution has yet been devised and thus it is an active research issue. The main challenges for vision-based vehicle detection and tracking are the high variability among vehicles, the dynamically changing background due to camera motion and the real-time processing requirement. In this thesis, a unified approach using statistical methods is presented for vehicle detection and tracking that tackles these issues. The approach is divided into three primary tasks, i.e., vehicle hypothesis generation, hypothesis verification, and vehicle tracking, which are performed sequentially. Nevertheless, the exchange of information between processing blocks is fostered so that the maximum degree of adaptation to changes in the environment can be achieved and the computational cost is alleviated. Two complementary strategies are proposed to address the first task, i.e., hypothesis generation, based respectively on appearance and geometry analysis. To this end, the use of a rectified domain in which the perspective is removed from the original image is especially interesting, as it allows for fast image scanning and coarse hypothesis generation. The final vehicle candidates are produced using a collaborative framework between the original and the rectified domains. A supervised classification strategy is adopted for the verification of the hypothesized vehicle locations. In particular, state-of-the-art methods for feature extraction are evaluated and new descriptors are proposed by exploiting the knowledge on vehicle appearance. Due to the lack of appropriate public databases, a new database is generated and the classification performance of the descriptors is extensively tested on it. Finally, a methodology for the fusion of the different classifiers is presented and the best combinations are discussed. The core of the proposed approach is a Bayesian tracking framework using particle filters. Contributions are made on its three key elements: the inference algorithm, the dynamic model and the observation model. In particular, the use of a Markov chain Monte Carlo method is proposed for sampling, which circumvents the exponential complexity increase of traditional particle filters thus making joint multiple vehicle tracking affordable. On the other hand, the aforementioned rectified domain allows for the definition of a constant-velocity dynamic model since it preserves the smooth motion of vehicles in highways. Finally, a multiple-cue observation model is proposed that not only accounts for vehicle appearance but also integrates the available information from the analysis in the previous blocks. The proposed approach is proven to run near real-time in a general purpose PC and to deliver outstanding results compared to traditional methods.

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A compact planar array with parasitic elements is studied to be used in MIMO systems. Classical compact arrays suffer from high coupling which makes correlation and matching efficiency to be worse. A proper matching network improves these lacks although its bandwidth is low and may increase the antenna size. The proposed antenna makes use of parasitic elements to improve both correlation and efficiency. A specific software based on MoM has been developed to analyze radiating structures with several feed points. The array is optimized through a Genetic Algorithm to determine parasitic elements position in order to fulfill different figures of merit. The proposed design provides the required correlation and matching efficiency to have a good performance over a significant bandwidth.

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A planar antenna is introduced that works as a portable system for X-band satellite communications. This antenna is low-profile and modular with dimensions of 40 × 40 × 2.5 × cm. It is composed of a square array of 144 printed circuit elements that cover a wide bandwidth (14.7%) for transmission and reception along with dual and interchangeable circular polarization. A radiation efficiency above 50% is achieved by a low-loss stripline feeding network. This printed antenna has a 3 dB beamwidth of 5°, a maximum gain of 26 dBi and an axial ratio under 1.9 dB over the entire frequency band. The complete design of the antenna is shown, and the measurements are compared with simulations to reveal very good agreement.

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Multi-camera 3D tracking systems with overlapping cameras represent a powerful mean for scene analysis, as they potentially allow greater robustness than monocular systems and provide useful 3D information about object location and movement. However, their performance relies on accurately calibrated camera networks, which is not a realistic assumption in real surveillance environments. Here, we introduce a multi-camera system for tracking the 3D position of a varying number of objects and simultaneously refin-ing the calibration of the network of overlapping cameras. Therefore, we introduce a Bayesian framework that combines Particle Filtering for tracking with recursive Bayesian estimation methods by means of adapted transdimensional MCMC sampling. Addi-tionally, the system has been designed to work on simple motion detection masks, making it suitable for camera networks with low transmission capabilities. Tests show that our approach allows a successful performance even when starting from clearly inaccurate camera calibrations, which would ruin conventional approaches.

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This paper presents a general systems that can be taken into account to control between elements in an antenna array. Because the digital phase shifter devices have become a strategic element and also some steps have been taken for their export by U.S. Government, this element has increased its price to the low supply in the market. Therefore, it is necessary to adopt some solutions that allow us to deal with the design and construction of antenna arrays. system based on a group of a staggered phase shift with external switching is shown, which is extrapolated array.

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The main purpose of robot calibration is the correction of the possible errors in the robot parameters. This paper presents a method for a kinematic calibration of a parallel robot that is equipped with one camera in hand. In order to preserve the mechanical configuration of the robot, the camera is utilized to acquire incremental positions of the end effector from a spherical object that is fixed in the word reference frame. The positions of the end effector are related to incremental positions of resolvers of the motors of the robot, and a kinematic model of the robot is used to find a new group of parameters which minimizes errors in the kinematic equations. Additionally, properties of the spherical object and intrinsic camera parameters are utilized to model the projection of the object in the image and improving spatial measurements. Finally, the robotic system is designed to carry out tracking tasks and the calibration of the robot is validated by means of integrating the errors of the visual controller.

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Nowadays, more a more base stations are equipped with active conformal antennas. These antenna designs combine phase shift systems with multibeam networks providing multi-beam ability and interference rejection, which optimize multiple channel systems. GEODA is a conformal adaptive antenna system designed for satellite communications. Operating at 1.7 GHz with circular polarization, it is possible to track and communicate with several satellites at once thanks to its adaptive beam. The antenna is based on a set of similar triangular arrays that are divided in subarrays of three elements called `cells'. Transmission/Receiver (T/R) modules manage beam steering by shifting the phases. A more accurate steering of the antenna GEODA could be achieved by using a multibeam network. Several multibeam network designs based on Butler network will be presented

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A multibeam antenna study based on Butler network will be undertaken in this document. These antenna designs combines phase shift systems with multibeam networks to optimize multiple channel systems. The system will work at 1.7 GHz with circular polarization. Specifically, result simulations and measurements of 3 element triangular subarray will be shown. A 45 element triangular array will be formed by the subarrays. Using triangular subarrays, side lobes and crossing points are reduced.

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A six inputs and three outputs structure which can be used to obtain six simultaneous beams with a triangular array of 3 elements is presented. The beam forming network is obtained combining balanced and unbalanced hybrid couplers and allows to obtain six main beams with sixty degrees of separation in azimuth direction. Simulations and measurements showing the performance of the array and other detailed results are presented

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In this paper we present a scalable software architecture for on-line multi-camera video processing, that guarantees a good trade off between computational power, scalability and flexibility. The software system is modular and its main blocks are the Processing Units (PUs), and the Central Unit. The Central Unit works as a supervisor of the running PUs and each PU manages the acquisition phase and the processing phase. Furthermore, an approach to easily parallelize the desired processing application has been presented. In this paper, as case study, we apply the proposed software architecture to a multi-camera system in order to efficiently manage multiple 2D object detection modules in a real-time scenario. System performance has been evaluated under different load conditions such as number of cameras and image sizes. The results show that the software architecture scales well with the number of camera and can easily works with different image formats respecting the real time constraints. Moreover, the parallelization approach can be used in order to speed up the processing tasks with a low level of overhead

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In this paper we present an adaptive multi-camera system for real time object detection able to efficiently adjust the computational requirements of video processing blocks to the available processing power and the activity of the scene. The system is based on a two level adaptation strategy that works at local and at global level. Object detection is based on a Gaussian mixtures model background subtraction algorithm. Results show that the system can efficiently adapt the algorithm parameters without a significant loss in the detection accuracy.

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A compact array of monopoles with a slotted ground plane is analyzed for being used in MIMO systems. Compact arrays suffer usually from high coupling which degrades significantly MIMO benefits. Through a matching network, main drawbacks can be solved, although it tends to provide a low bandwidth. The studied design is an array of monopoles with a slot in the ground plane. The slot shape is optimized with a Genetic Algorithm and an own electromagnetic software based on MoM in order to fulfill main figures of merit within a significant bandwidth