Mala gente que camina : De la expropiación a la reconstrucción de la memoria

Las indagaciones de la última década sobre el robo de niños en la dictadura franquista y el silencio por parte de los gobiernos democráticos españoles, han despertado el interés tanto de historiadores como de escritores. Quienes no vivieron directamente el exterminio físico e ideológico del régimen dictatorial, recomponen las identidades que quedaron sepultadas en fosas comunes, pero también esclarecen las apropiaciones por parte del Estado, para que aquellos que aún viven engañados puedan saberlo. Benjamín Prado con Mala gente que camina, se inscribe en el conjunto de autores que trabajan por escribir una memoria histórica capaz de llenar los vacíos que han dejado las generaciones anteriores

Near-coastal circum-Antarctic iceberg size distributions determined from Synthetic Aperture Radar images

The Radarsat-1 Antarctic Mapping Project (RAMP) compiled a mosaic of Antarctica and the adjacent ocean zone from more than 3000 high-resolution Synthetic Aperture Radar (SAR) images acquired in September and October 1997. The mosaic with a pixel size of 100 m was used to determine iceberg size distributions around Antarctica, combining an automated detection with a visual control of all icebergs larger than 5 km**2 and correction of recognized false detections. For icebergs below 5 km**2 in size, the numbers of false detections and accuracies of size retrievals were analyzed for three test sites. Nearly 7000 icebergs with horizontal areas between 0.3 and 4717.7 km**2 were identified in a near-coastal zone of varying width between 20 and 300 km. The spatial distributions of icebergs around Antarctica were calculated for zonal segments of 20° angular width and related to the types of the calving fronts in the respective section. Results reveal that regional variations of the size distributions cannot be neglected. The highest ice mass accumulations were found at positions of giant icebergs (> 18.5 km) but also in front of ice shelves from which larger numbers of smaller icebergs calve almost continuously. Although the coastal oceanic zone covered by RAMP is too narrow compared to the spatial coverage needed for oceanographic research, this study nevertheless demonstrates the usefulness of SAR images for iceberg research and the need for repeated data acquisitions extending ocean-wards over distances of 500 km and more from the coast to monitor iceberg melt and disintegration and the related freshwater input into the ocean.

Daily pan-Arctic sea-ice lead maps for 2003-2015, with links to maps in netCDF format

The presence of sea-ice leads represents a key feature of the Arctic sea ice cover. Leads promote the flux of sensible and latent heat from the ocean to the cold winter atmosphere and are thereby crucial for air-sea-ice-ocean interactions. We here apply a binary segmentation procedure to identify leads from MODIS thermal infrared imagery on a daily time scale. The method separates identified leads into two uncertainty categories, with the high uncertainty being attributed to artifacts that arise from warm signatures of unrecognized clouds. Based on the obtained lead detections, we compute quasi-daily pan-Arctic lead maps for the months of January to April, 2003-2015. Our results highlight the marginal ice zone in the Fram Strait and Barents Sea as the primary region for lead activity. The spatial distribution of the average pan-Arctic lead frequencies reveals, moreover, distinct patterns of predominant fracture zones in the Beaufort Sea and along the shelf-breaks, mainly in the Siberian sector of the Arctic Ocean as well as the well-known polynya and fast-ice locations. Additionally, a substantial inter-annual variability of lead occurrences in the Arctic is indicated.

Segmentación de Secuencias de Vídeo: análisis y desarrollo de estrategias para la detección de cambios de toma y para la detección de objetos móviles

The important technological advances experienced along the last years have resulted in an important demand for new and efficient computer vision applications. On the one hand, the increasing use of video editing software has given rise to a necessity for faster and more efficient editing tools that, in a first step, perform a temporal segmentation in shots. On the other hand, the number of electronic devices with integrated cameras has grown enormously. These devices require new, fast, and efficient computer vision applications that include moving object detection strategies. In this dissertation, we propose a temporal segmentation strategy and several moving object detection strategies, which are suitable for the last generation of computer vision applications requiring both low computational cost and high quality results. First, a novel real-time high-quality shot detection strategy is proposed. While abrupt transitions are detected through a very fast pixel-based analysis, gradual transitions are obtained from an efficient edge-based analysis. Both analyses are reinforced with a motion analysis that allows to detect and discard false detections. This analysis is carried out exclusively over a reduced amount of candidate transitions, thus maintaining the computational requirements. On the other hand, a moving object detection strategy, which is based on the popular Mixture of Gaussians method, is proposed. This strategy, taking into account the recent history of each image pixel, adapts dynamically the amount of Gaussians that are required to model its variations. As a result, we improve significantly the computational efficiency with respect to other similar methods and, additionally, we reduce the influence of the used parameters in the results. Alternatively, in order to improve the quality of the results in complex scenarios containing dynamic backgrounds, we propose different non-parametric based moving object detection strategies that model both background and foreground. To obtain high quality results regardless of the characteristics of the analyzed sequence we dynamically estimate the most adequate bandwidth matrices for the kernels that are used in the background and foreground modeling. Moreover, the application of a particle filter allows to update the spatial information and provides a priori knowledge about the areas to analyze in the following images, enabling an important reduction in the computational requirements and improving the segmentation results. Additionally, we propose the use of an innovative combination of chromaticity and gradients that allows to reduce the influence of shadows and reflects in the detections.

Detection and Tracking of Traffic Signs Using a Recursive Bayesian Decision Framework

In this paper we propose a new method for the automatic detection and tracking of road traffic signs using an on-board single camera. This method aims to increase the reliability of the detections such that it can boost the performance of any traffic sign recognition scheme. The proposed approach exploits a combination of different features, such as color, appearance, and tracking information. This information is introduced into a recursive Bayesian decision framework, in which prior probabilities are dynamically adapted to tracking results. This decision scheme obtains a number of candidate regions in the image, according to their HS (Hue-Saturation). Finally, a Kalman filter with an adaptive noise tuning provides the required time and spatial coherence to the estimates. Results have shown that the proposed method achieves high detection rates in challenging scenarios, including illumination changes, rapid motion and significant perspective distortion

An Efficient Multiple Object Detection and Tracking Framework for Automatic Counting and Video Surveillance Applications

Automatic visual object counting and video surveillance have important applications for home and business environments, such as security and management of access points. However, in order to obtain a satisfactory performance these technologies need professional and expensive hardware, complex installations and setups, and the supervision of qualified workers. In this paper, an efficient visual detection and tracking framework is proposed for the tasks of object counting and surveillance, which meets the requirements of the consumer electronics: off-the-shelf equipment, easy installation and configuration, and unsupervised working conditions. This is accomplished by a novel Bayesian tracking model that can manage multimodal distributions without explicitly computing the association between tracked objects and detections. In addition, it is robust to erroneous, distorted and missing detections. The proposed algorithm is compared with a recent work, also focused on consumer electronics, proving its superior performance.

Automatic Bandwidth Estimation Strategy for High-Quality Non-Parametric Modeling based Moving Object Detection

Here, a novel and efficient moving object detection strategy by non-parametric modeling is presented. Whereas the foreground is modeled by combining color and spatial information, the background model is constructed exclusively with color information, thus resulting in a great reduction of the computational and memory requirements. The estimation of the background and foreground covariance matrices, allows us to obtain compact moving regions while the number of false detections is reduced. Additionally, the application of a tracking strategy provides a priori knowledge about the spatial position of the moving objects, which improves the performance of the Bayesian classifier

Accurate pedestrian indoor navigation by tightly coupling foot-mounted IMU and RFID measurements

We present a new method to accurately locate persons indoors by fusing inertial navigation system (INS) techniques with active RFID technology. A foot-mounted inertial measuring units (IMUs)-based position estimation method, is aided by the received signal strengths (RSSs) obtained from several active RFID tags placed at known locations in a building. In contrast to other authors that integrate IMUs and RSS with a loose Kalman filter (KF)-based coupling (by using the residuals of inertial- and RSS-calculated positions), we present a tight KF-based INS/RFID integration, using the residuals between the INS-predicted reader-to-tag ranges and the ranges derived from a generic RSS path-loss model. Our approach also includes other drift reduction methods such as zero velocity updates (ZUPTs) at foot stance detections, zero angular-rate updates (ZARUs) when the user is motionless, and heading corrections using magnetometers. A complementary extended Kalman filter (EKF), throughout its 15-element error state vector, compensates the position, velocity and attitude errors of the INS solution, as well as IMU biases. This methodology is valid for any kind of motion (forward, lateral or backward walk, at different speeds), and does not require an offline calibration for the user gait. The integrated INS+RFID methodology eliminates the typical drift of IMU-alone solutions (approximately 1% of the total traveled distance), resulting in typical positioning errors along the walking path (no matter its length) of approximately 1.5 m.

Localization and Tracking in Energy-Constrained Networks with Dynamic Connectivity

Systems used for target localization, such as goods, individuals, or animals, commonly rely on operational means to meet the final application demands. However, what would happen if some means were powered up randomly by harvesting systems? And what if those devices not randomly powered had their duty cycles restricted? Under what conditions would such an operation be tolerable in localization services? What if the references provided by nodes in a tracking problem were distorted? Moreover, there is an underlying topic common to the previous questions regarding the transfer of conceptual models to reality in field tests: what challenges are faced upon deploying a localization network that integrates energy harvesting modules? The application scenario of the system studied is a traditional herding environment of semi domesticated reindeer (Rangifer tarandus tarandus) in northern Scandinavia. In these conditions, information on approximate locations of reindeer is as important as environmental preservation. Herders also need cost-effective devices capable of operating unattended in, sometimes, extreme weather conditions. The analyses developed are worthy not only for the specific application environment presented, but also because they may serve as an approach to performance of navigation systems in absence of reasonably accurate references like the ones of the Global Positioning System (GPS). A number of energy-harvesting solutions, like thermal and radio-frequency harvesting, do not commonly provide power beyond one milliwatt. When they do, battery buffers may be needed (as it happens with solar energy) which may raise costs and make systems more dependent on environmental temperatures. In general, given our problem, a harvesting system is needed that be capable of providing energy bursts of, at least, some milliwatts. Many works on localization problems assume that devices have certain capabilities to determine unknown locations based on range-based techniques or fingerprinting which cannot be assumed in the approach considered herein. The system presented is akin to range-free techniques, but goes to the extent of considering very low node densities: most range-free techniques are, therefore, not applicable. Animal localization, in particular, uses to be supported by accurate devices such as GPS collars which deplete batteries in, maximum, a few days. Such short-life solutions are not particularly desirable in the framework considered. In tracking, the challenge may times addressed aims at attaining high precision levels from complex reliable hardware and thorough processing techniques. One of the challenges in this Thesis is the use of equipment with just part of its facilities in permanent operation, which may yield high input noise levels in the form of distorted reference points. The solution presented integrates a kinetic harvesting module in some nodes which are expected to be a majority in the network. These modules are capable of providing power bursts of some milliwatts which suffice to meet node energy demands. The usage of harvesting modules in the aforementioned conditions makes the system less dependent on environmental temperatures as no batteries are used in nodes with harvesters--it may be also an advantage in economic terms. There is a second kind of nodes. They are battery powered (without kinetic energy harvesters), and are, therefore, dependent on temperature and battery replacements. In addition, their operation is constrained by duty cycles in order to extend node lifetime and, consequently, their autonomy. There is, in turn, a third type of nodes (hotspots) which can be static or mobile. They are also battery-powered, and are used to retrieve information from the network so that it is presented to users. The system operational chain starts at the kinetic-powered nodes broadcasting their own identifier. If an identifier is received at a battery-powered node, the latter stores it for its records. Later, as the recording node meets a hotspot, its full record of detections is transferred to the hotspot. Every detection registry comprises, at least, a node identifier and the position read from its GPS module by the battery-operated node previously to detection. The characteristics of the system presented make the aforementioned operation own certain particularities which are also studied. First, identifier transmissions are random as they depend on movements at kinetic modules--reindeer movements in our application. Not every movement suffices since it must overcome a certain energy threshold. Second, identifier transmissions may not be heard unless there is a battery-powered node in the surroundings. Third, battery-powered nodes do not poll continuously their GPS module, hence localization errors rise even more. Let's recall at this point that such behavior is tight to the aforementioned power saving policies to extend node lifetime. Last, some time is elapsed between the instant an identifier random transmission is detected and the moment the user is aware of such a detection: it takes some time to find a hotspot. Tracking is posed as a problem of a single kinetically-powered target and a population of battery-operated nodes with higher densities than before in localization. Since the latter provide their approximate positions as reference locations, the study is again focused on assessing the impact of such distorted references on performance. Unlike in localization, distance-estimation capabilities based on signal parameters are assumed in this problem. Three variants of the Kalman filter family are applied in this context: the regular Kalman filter, the alpha-beta filter, and the unscented Kalman filter. The study enclosed hereafter comprises both field tests and simulations. Field tests were used mainly to assess the challenges related to power supply and operation in extreme conditions as well as to model nodes and some aspects of their operation in the application scenario. These models are the basics of the simulations developed later. The overall system performance is analyzed according to three metrics: number of detections per kinetic node, accuracy, and latency. The links between these metrics and the operational conditions are also discussed and characterized statistically. Subsequently, such statistical characterization is used to forecast performance figures given specific operational parameters. In tracking, also studied via simulations, nonlinear relationships are found between accuracy and duty cycles and cluster sizes of battery-operated nodes. The solution presented may be more complex in terms of network structure than existing solutions based on GPS collars. However, its main gain lies on taking advantage of users' error tolerance to reduce costs and become more environmentally friendly by diminishing the potential amount of batteries that can be lost. Whether it is applicable or not depends ultimately on the conditions and requirements imposed by users' needs and operational environments, which is, as it has been explained, one of the topics of this Thesis.

Highly correlated ab initio study of the far infrared spectra of methyl acetate

Highly correlated ab initio calculations (CCSD(T)) are used to compute gas phase spectroscopic parameters of three isotopologues of the methyl acetate (CH3COOCH3, CD3COOCH3, and CH3COOCD3), searching to help experimental assignments and astrophysical detections. The molecule shows two conformers cis and trans separated by a barrier of 4457 cm−1. The potential energy surface presents 18 minima that intertransform through three internal rotation motions. To analyze the far infrared spectrum at low temperatures, a three-dimensional Hamiltonian is solved variationally. The two methyl torsion barriers are calculated to be 99.2 cm−1 (C–CH3) and 413.1 cm−1 (O–CH3), for the cis-conformer. The three fundamental torsional band centers of CH3COOCH3 are predicted to lie at 63.7 cm−1 (C–CH3), 136.1 cm−1 (O–CH3), and 175.8 cm−1 (C–O torsion) providing torsional state separations. For the 27 vibrational modes, anharmonic fundamentals and rovibrational parameters are provided. Computed parameters are compared with those fitted using experimental data.

Higher-order regularization and morphological techniques for image segmentation

La segmentación de imágenes es un campo importante de la visión computacional y una de las áreas de investigación más activas, con aplicaciones en comprensión de imágenes, detección de objetos, reconocimiento facial, vigilancia de vídeo o procesamiento de imagen médica. La segmentación de imágenes es un problema difícil en general, pero especialmente en entornos científicos y biomédicos, donde las técnicas de adquisición imagen proporcionan imágenes ruidosas. Además, en muchos de estos casos se necesita una precisión casi perfecta. En esta tesis, revisamos y comparamos primero algunas de las técnicas ampliamente usadas para la segmentación de imágenes médicas. Estas técnicas usan clasificadores a nivel de pixel e introducen regularización sobre pares de píxeles que es normalmente insuficiente. Estudiamos las dificultades que presentan para capturar la información de alto nivel sobre los objetos a segmentar. Esta deficiencia da lugar a detecciones erróneas, bordes irregulares, configuraciones con topología errónea y formas inválidas. Para solucionar estos problemas, proponemos un nuevo método de regularización de alto nivel que aprende información topológica y de forma a partir de los datos de entrenamiento de una forma no paramétrica usando potenciales de orden superior. Los potenciales de orden superior se están popularizando en visión por computador, pero la representación exacta de un potencial de orden superior definido sobre muchas variables es computacionalmente inviable. Usamos una representación compacta de los potenciales basada en un conjunto finito de patrones aprendidos de los datos de entrenamiento que, a su vez, depende de las observaciones. Gracias a esta representación, los potenciales de orden superior pueden ser convertidos a potenciales de orden 2 con algunas variables auxiliares añadidas. Experimentos con imágenes reales y sintéticas confirman que nuestro modelo soluciona los errores de aproximaciones más débiles. Incluso con una regularización de alto nivel, una precisión exacta es inalcanzable, y se requeire de edición manual de los resultados de la segmentación automática. La edición manual es tediosa y pesada, y cualquier herramienta de ayuda es muy apreciada. Estas herramientas necesitan ser precisas, pero también lo suficientemente rápidas para ser usadas de forma interactiva. Los contornos activos son una buena solución: son buenos para detecciones precisas de fronteras y, en lugar de buscar una solución global, proporcionan un ajuste fino a resultados que ya existían previamente. Sin embargo, requieren una representación implícita que les permita trabajar con cambios topológicos del contorno, y esto da lugar a ecuaciones en derivadas parciales (EDP) que son costosas de resolver computacionalmente y pueden presentar problemas de estabilidad numérica. Presentamos una aproximación morfológica a la evolución de contornos basada en un nuevo operador morfológico de curvatura que es válido para superficies de cualquier dimensión. Aproximamos la solución numérica de la EDP de la evolución de contorno mediante la aplicación sucesiva de un conjunto de operadores morfológicos aplicados sobre una función de conjuntos de nivel. Estos operadores son muy rápidos, no sufren de problemas de estabilidad numérica y no degradan la función de los conjuntos de nivel, de modo que no hay necesidad de reinicializarlo. Además, su implementación es mucho más sencilla que la de las EDP, ya que no requieren usar sofisticados algoritmos numéricos. Desde un punto de vista teórico, profundizamos en las conexiones entre operadores morfológicos y diferenciales, e introducimos nuevos resultados en este área. Validamos nuestra aproximación proporcionando una implementación morfológica de los contornos geodésicos activos, los contornos activos sin bordes, y los turbopíxeles. En los experimentos realizados, las implementaciones morfológicas convergen a soluciones equivalentes a aquéllas logradas mediante soluciones numéricas tradicionales, pero con ganancias significativas en simplicidad, velocidad y estabilidad. ABSTRACT Image segmentation is an important field in computer vision and one of its most active research areas, with applications in image understanding, object detection, face recognition, video surveillance or medical image processing. Image segmentation is a challenging problem in general, but especially in the biological and medical image fields, where the imaging techniques usually produce cluttered and noisy images and near-perfect accuracy is required in many cases. In this thesis we first review and compare some standard techniques widely used for medical image segmentation. These techniques use pixel-wise classifiers and introduce weak pairwise regularization which is insufficient in many cases. We study their difficulties to capture high-level structural information about the objects to segment. This deficiency leads to many erroneous detections, ragged boundaries, incorrect topological configurations and wrong shapes. To deal with these problems, we propose a new regularization method that learns shape and topological information from training data in a nonparametric way using high-order potentials. High-order potentials are becoming increasingly popular in computer vision. However, the exact representation of a general higher order potential defined over many variables is computationally infeasible. We use a compact representation of the potentials based on a finite set of patterns learned fromtraining data that, in turn, depends on the observations. Thanks to this representation, high-order potentials can be converted into pairwise potentials with some added auxiliary variables and minimized with tree-reweighted message passing (TRW) and belief propagation (BP) techniques. Both synthetic and real experiments confirm that our model fixes the errors of weaker approaches. Even with high-level regularization, perfect accuracy is still unattainable, and human editing of the segmentation results is necessary. The manual edition is tedious and cumbersome, and tools that assist the user are greatly appreciated. These tools need to be precise, but also fast enough to be used in real-time. Active contours are a good solution: they are good for precise boundary detection and, instead of finding a global solution, they provide a fine tuning to previously existing results. However, they require an implicit representation to deal with topological changes of the contour, and this leads to PDEs that are computationally costly to solve and may present numerical stability issues. We present a morphological approach to contour evolution based on a new curvature morphological operator valid for surfaces of any dimension. We approximate the numerical solution of the contour evolution PDE by the successive application of a set of morphological operators defined on a binary level-set. These operators are very fast, do not suffer numerical stability issues, and do not degrade the level set function, so there is no need to reinitialize it. Moreover, their implementation is much easier than their PDE counterpart, since they do not require the use of sophisticated numerical algorithms. From a theoretical point of view, we delve into the connections between differential andmorphological operators, and introduce novel results in this area. We validate the approach providing amorphological implementation of the geodesic active contours, the active contours without borders, and turbopixels. In the experiments conducted, the morphological implementations converge to solutions equivalent to those achieved by traditional numerical solutions, but with significant gains in simplicity, speed, and stability.

Efficient hybrid monocular-stereo approach to on-board, video-based traffic sign detection and tracking

In this paper we propose an innovative method for the automatic detection and tracking of road traffic signs using an onboard stereo camera. It involves a combination of monocular and stereo analysis strategies to increase the reliability of the detections such that it can boost the performance of any traffic sign recognition scheme. Firstly, an adaptive color and appearance based detection is applied at single camera level to generate a set of traffic sign hypotheses. In turn, stereo information allows for sparse 3D reconstruction of potential traffic signs through a SURF-based matching strategy. Namely, the plane that best fits the cloud of 3D points traced back from feature matches is estimated using a RANSAC based approach to improve robustness to outliers. Temporal consistency of the 3D information is ensured through a Kalman-based tracking stage. This also allows for the generation of a predicted 3D traffic sign model, which is in turn used to enhance the previously mentioned color-based detector through a feedback loop, thus improving detection accuracy. The proposed solution has been tested with real sequences under several illumination conditions and in both urban areas and highways, achieving very high detection rates in challenging environments, including rapid motion and significant perspective distortion

Temporal segmentation tool for high-quality real time video editing software

The increasing use of video editing software requires faster and more efficient editing tools. As a first step, these tools perform a temporal segmentation in shots that allows a later building of indexes describing the video content. Here, we propose a novel real-time high-quality shot detection strategy, suitable for the last generation of video editing software requiring both low computational cost and high quality results. While abrupt transitions are detected through a very fast pixel-based analysis, gradual transitions are obtained from an efficient edge-based analysis. Both analyses are reinforced with a motion analysis that helps to detect and discard false detections. This motion analysis is carried out exclusively over a reduced set of candidate transitions, thus maintaining the computational requirements demanded by new applications to fulfill user needs.

A new analog trigger system for the Cherenkov Telescope array

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.

Real-time Surveillance Application by Multiple Detectors and Compressive Trackers

A real-time surveillance system for IP network cameras is presented. Motion, part-body, and whole-body detectors are efficiently combined to generate robust and fast detections, which feed multiple compressive trackers. The generated trajectories are then improved using a reidentification strategy for long term operation.