Improving Multiple-Model Context-Aided Tracking through an Autocorrelation Approach

Proceedings of: 15th International Conference on Information Fusion (FUSION), Singapore, 9-12 July 2012This paper continues a previous work, where the context-aided tracker "ConTracker" was used to detect suspicious behaviors in maritime vehicle trajectories. ConTracker takes into account map-based contextual information - which includes water depth, shipping channels and areas/buildings with a high strategy value - to determine anomalies in ship trajectories. The different areas act as repellers or attractors that modify the expected trajectory of the tracked vessel. In the original scheme, a multiple-model adaptive estimator (MMAE) is used to estimate the noise parameters of the tracking system: sudden increases on the output reflect unexpected maneuvers - such as entering a forbidden area - that are translated as alarms. The work presented here shows the results obtained by implementing a generalized version of the multiple-model adaptive estimator (GMMAE). While the former approach uses information of the last cycle to update the weight/importance of each model, our proposal calculates a likelihood value based on the time-domain autocorrelation function of the last few indicators. GMMAE provides a much faster response, which ultimately leads to a general performance boost: alarms are faster and clearer. Compared with previous works, GMMAE is particularly effective returning back to normal state after an alarm has been raised: this results in alarms with a better defined duration. Results are presented over several simulated trajectories, featuring a variety of realistic anomalies which are correctly identified. They include direct comparison with the previous approach, for an objective demonstration of the achieved improvement.This work was supported in part by Projects CICYT TIN2011-28620-C02-01, CICYT TEC2011-28626-C02- 02, CAM CONTEXTS (S2009/TIC-1485) and DPS2008- 07029-C02-02.Publicad

Analysis of a sensor fusion hybrid solution for indoor/outdoor robot navigation

Proceedings of: 5th ESA Workshop on Satellite Navigation Technologies and European Workshop on GNSS Signals and Signal Processing (NAVITEC 2010). Noordwij, Netherlands, 8-10 December 2010Autonomous mobile robots need robust, flexible and accurate navigation algorithms. One approach consists in fusing as many information sources as possible, integrating measures from internal sensors with data obtained from external sensing entities. This work presents a solution for combined indoor/outdoor robot navigation, and analyzes some preliminary results in an outdoor environment using a Particle Filter for GPS/INS sensor fusion. Experiments are based in predesigned trajectories which have been simulated in first place and then reproduced using a robotic platform. As a concluding remark, some considerations about the use of Particle Filters and the differences between simulated and real data are presentedThis work was supported in part by Projects ATLANTIDA, CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008- 06732-C02-02/TEC, SINPROB, CAM MADRINET S- 0505/TIC/0255 DPS2008-07029-C02-02.Publicad

Neighborhood-based Regularization of Proposal Distribution for Improving Resampling Quality in Particle Filters

Proceedings of: 14th International Conference on Information Fusion (FUSION 2011). Chicago, Illinois, USA 5-8 July 2011Particle Filter is a sequential Montecarlo algorithm extensively used for solving estimation problems with non-linear and non-Gaussian features. In spite of its relative simplicity, it is known to suffer some undesired effects that can spoil its performance. Among these problems we can account the one known as sample depletion. This paper reviews the different causes of sample depletion and the many solutions proposed in the existing literature. It also introduces a new strategy for particle resampling which relies in a local linearization of the proposal distribution. The particles drawn using the proposed method are not affected by sample impoverishment and can indirectly lead to better results thanks to a reduction in the plant noise employed, as well to increased performance because of requiring a lower number of particles to achieve same results.Publicad

A framework for context-aware sensor fusion

Mención Internacional en el título de doctorSensor fusion is a mature but very active research field, included in the more general discipline of information fusion. It studies how to combine data coming from different sensors, in such way that the resulting information is better in some sense –more complete, accurate or stable– than any of the original sources used individually. Context is defined as everything that constraints or affects the process of solving a problem, without being part of the problem or the solution itself. Over the last years, the scientific community has shown a remarkable interest in the potential of exploiting this context information for building smarter systems that can make a better use of the available information. Traditional sensor fusion systems are based in fixed processing schemes over a predefined set of sensors, where both the employed algorithms and domain are assumed to remain unchanged over time. Nowadays, affordable mobile and embedded systems have a high sensory, computational and communication capabilities, making them a perfect base for building sensor fusion applications. This fact represents an opportunity to explore fusion system that are bigger and more complex, but pose the challenge of offering optimal performance under changing and unexpected circumstances. This thesis proposes a framework supporting the creation of sensor fusion systems with self-adaptive capabilities, where context information plays a crucial role. These two aspects have never been integrated in a common approach for solving the sensor fusion problem before. The proposal includes a preliminary theoretical analysis of both problem aspects, the design of a generic architecture capable for hosting any type of centralized sensor fusion application, and a description of the process to be followed for applying the architecture in order to solve a sensor fusion problem. The experimental section shows how to apply this thesis’ proposal, step by step, for creating a context-aware sensor fusion system with self-adaptive capabilities. This process is illustrated for two different domains: a maritime/coastal surveillance application, and ground vehicle navigation in urban environment. Obtained results demonstrate the viability and validity of the implemented prototypes, as well as the benefit of including context information to enhance sensor fusion processes.La fusión de sensores es un campo de investigación maduro pero no por ello menos activo, que se engloba dentro de la disciplina más amplia de la fusión de información. Su papel consiste en mezclar información de dispositivos sensores para proporcionar un resultado que mejora en algún aspecto –completitud, precisión, estabilidad– al que se puede obtener de las diversas fuentes por separado. Definimos contexto como todo aquello que restringe o afecta el proceso de resolución de un problema, sin ser parte del problema o de su solución. En los últimos años, la comunidad científica ha demostrado un gran interés en el potencial que ofrece el contexto para construir sistemas más inteligentes, capaces de hacer un mejor uso de la información disponible. Por otro lado, el desarrollo de sistemas de fusión de sensores ha respondido tradicionalmente a esquemas de procesado poco flexibles sobre un conjunto prefijado de sensores, donde los algoritmos y el dominio de problema permanecen inalterados con el paso del tiempo. En la actualidad, el abaratamiento de dispositivos móviles y embebidos con gran capacidad sensorial, de comunicación y de procesado plantea nuevas oportunidades. La comunidad científica comienza a explorar la creación de sistemas con mayor grado de complejidad y autonomía, que sean capaces de adaptarse a circunstancias inesperadas y ofrecer un rendimiento óptimo en cada caso. En esta tesis se propone un framework que permite crear sistemas de fusión de sensores con capacidad de auto-adaptación, donde la información contextual juega un papel fundamental. Hasta la fecha, ambos aspectos no han sido integrados en un enfoque conjunto. La propuesta incluye un análisis teórico de ambos aspectos del problema, el diseño de una arquitectura genérica capaz de dar cabida a cualquier aplicación de fusión de sensores centralizada, y la descripción del proceso a seguir para aplicar dicha arquitectura a cualquier problema de fusión de sensores. En la sección experimental se demuestra cómo aplicar nuestra propuesta, paso por paso, para crear un sistema de fusión de sensores adaptable y sensible al contexto. Este proceso de diseño se ilustra sobre dos problemas pertenecientes a dominios tan distintos como la vigilancia costera y la navegación de vehículos en entornos urbanos. El análisis de resultados incluye experimentos concretos que demuestran la validez de los prototipos implementados, así como el beneficio de usar información contextual para mejorar los procesos de fusión de sensores.Programa Oficial de Doctorado en Ciencia y Tecnología InformáticaPresidente: Javier Bajo Pérez.- Secretario: Antonio Berlanga de Jesús.- Vocal: Lauro Snidar

Proper motions of young stars in Chamaeleon. I. A Virtual Observatory study of spectroscopically confirmed members

(abridged) We want to provide further evidence of the origin of the proposed stellar members of Chamaeleon and to identify interlopers from the foreground \epsilon Cha and \eta Cha associations. To this aim, we compile lists of spectroscopically confirmed members of Chamaeleon I and II, \epsilon Cha and \eta Cha, and of background objects in the same line of sight. Using Virtual Observatory tools, we cross-match these lists with the UCAC3 catalogue to get the proper motions of the objects. In the vector point diagram, we identify the different moving groups, and use this information to study the membership of proposed candidate members of the associations from the literature. For those objects with available radial velocities, we compute their Galactic space velocities. We look for correlations between the known properties of the objects and their proper motions. The members of the dark clouds exhibit clearly different proper motions from those of the foreground associations and of the background stars. The data suggest that Chamaeleon II could have different dynamical properties from Chamaeleon I. Although the two foreground clusters \epsilon and \eta Chamaeleontis constitute two different proper motion groups, they have similar spatial motions, which are different from the spatial motion of Chamaeleon I. On the other hand, the space motions of the Chamaeleon II stars look more similar to those of the foreground clusters than to the Chamaeleon I stars, but the numbers are low. Hence, with the available data it is unclear to what extent the stellar populations in both clouds are physically connected to each other. We find no correlations between the proper motions and the properties of the objects in either of the clouds

A Practical Case Study: Face Recognition on Low Quality Images Using Gabor Wavelet and Support Vector Machines

Face recognition is a problem that arises on many real world applications, such as those related with Ambient Intelligence (AmI). The specific nature and goals of AmI applications, however, requires minimizing the invasiveness of data collection methods, often resulting in a drastic reduction of data quality and a plague of unforeseen effects which can put standard face recognition systems out of action. In order to deal with this, a face recognition system for AmI applications must not only be carefully designed but also subject to an exhaustive configuration plan to ensure it offers the required accuracy, robustness and real-time performance. This document covers the design and tuning of a holistic face recognition system targeting an Ambient Intelligence scenario. It has to work under partially uncontrolled capturing conditions: frontal images with pose variation up to 40 degrees, changing illumination, variable image size and degraded quality. The proposed system is based on Support Vector Machine (SVM) classifiers and applies Gabor Filters intensively. A complete sensitivity analysis shows how the recognition accuracy can be boosted through careful configuration and proper parameter setting, although the most adequate setting depends on the requirements for the final system.This work was supported in part by Projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, SINPROB,CAMMADRINET S-0505 /TIC/0255 and DPS2008-07029-C02-02.Publicad

Predicted photoreflectance signatures on QD selective contacts for hot carrier solar cells

The CO2 emission of our present energy transformation processes, based mainly on burning fossil fuels, is possibly the main cause of global climatic change. The photovoltaic conversion of solar energy is a clean way of producing which for sustainability should (and most probably will) become a major source of electricity. The sun is a huge resource but relatively diluted and it is reasonable to expect that only high efficiency extraction can be cost effective for mass exploitation. New concepts are neccessary such as hot carrier solar cells

Fusion of Sensor Data and Intelligence in FITS

Proceedings of: 16th International Conference on Information Fusion (FUSION 2013): Istambul, Turkey 9-12 July 2013.The design and implementation of fusion systems working in real conditions requires functional and performance specification, analysis of information input and contextual domain, and development of testing and validation tools. This paper presents a fusion system recently developed to operate with EW and ISR sensors on-board of patrol aircraft, which must be fused with information from other collaborative entities and intelligence in databases. The paper describes the overall organization of the system developed, modules and the data flow. The characterization of data sources and core algorithms for data alignment, uncertainty representation and fusion management are detailed and validated in realistic situations.This work was supported in part by Projects FITS-DFS (EADS/CASA), MEyC TEC2012-37832-C02-01, MEyC TEC2011-28626-C02-02 and CAM CONTEXTS (S2009/TIC-1485).Publicad

Psicología positiva contemplativa: integrando mindfulness en la psicología positiva

A pesar de que mindfulness está integrado en muchos manuales de psicología positiva como una técnica 'positiva', apenas se han desarrollado las implicaciones que tiene su uso ni se ha investigado la relación entre mindfulness y bienestar humano. Analizar las principales potencialidades de los dos ámbitos, las posibilidades de integración, así como las posibles contradicciones entre sus mensajes, es fundamental de cara a establecer puentes. Mindfulness es más que una técnica de meditación, lleva implícitos una serie de valores y condicionantes éticos que se adecuan en buena medida con los presupuestos que se proponen desde la psicología positiva, como el desarrollo de la amabilidad, la compasión, y las emociones positivas. El objetivo de este artículo es presentar por un lado aspectos comunes y similitudes, y por otro lado diferencias entre mindfulness y la psicología positiva. También se presentarán los principales estudios que han investigado el papel que tiene mindfulness y las prácticas contemplativas sobre el bienestar humano. Finalmente se discutirá y plantearán futuras líneas de investigación e intervención para acercar ambas propuesta