Aplicación de gestión de oficinas de servicios de asistencia legal

[ES] El presente proyecto se postula como una posible solución de los distintos problemas de gestión que se encuentran los profesionales del sector jurídico durante la realización de su actividad laboral. Se plantean diversas alternativas, eligiendo como solución final implantar un sistema en Nube que le permita al usuario acceder a su información en cualquier momento y lugar. Dicha solución está constituida por cuatro componentes diferenciados (Servidor de Información, Aplicación de Escritorio, Aplicación móvil y Web), permitiendo al usuario poder utilizar el sistema en diversas plataformas. El diseño de los distintos elementos de la solución tendrá como características principales la seguridad, disponibilidad y usabilidad del sistema.

Optical flow estimation with consistent spatio-temporal coherence models

[EN] In this work we propose a new variational model for the consistent estimation of motion fields. The aim of this work is to develop appropriate spatio-temporal coherence models. In this sense, we propose two main contributions: a nonlinear flow constancy assumption, similar in spirit to the nonlinear brightness constancy assumption, which conveniently relates flow fields at different time instants; and a nonlinear temporal regularization scheme, which complements the spatial regularization and can cope with piecewise continuous motion fields. These contributions pose a congruent variational model since all the energy terms, except the spatial regularization, are based on nonlinear warpings of the flow field. This model is more general than its spatial counterpart, provides more accurate solutions and preserves the continuity of optical flows in time. In the experimental results, we show that the method attains better results and, in particular, it considerably improves the accuracy in the presence of large displacements.

TV-L1 optical flow estimation

[EN] This article describes an implementation of the optical flow estimation method introduced by Zach, Pock and Bischof. This method is based on the minimization of a functional containing a data term using the L norm and a regularization term using the total variation of the flow. The main feature of this formulation is that it allows discontinuities in the flow field, while being more robust to noise than the classical approach. The algorithm is an efficient numerical scheme, which solves a relaxed version of the problem by alternate minimization.

A subpixel edge detector applied to aortic dissection detection

[EN] The aortic dissection is a disease that can cause a deadly situation, even with a correct treatment. It consists in a rupture of a layer of the aortic artery wall, causing a blood flow inside this rupture, called dissection. The aim of this paper is to contribute to its diagnosis, detecting the dissection edges inside the aorta. A subpixel accuracy edge detector based on the hypothesis of partial volume effect is used, where the intensity of an edge pixel is the sum of the contribution of each color weighted by its relative area inside the pixel. The method uses a floating window centred on the edge pixel and computes the edge features. The accuracy of our method is evaluated on synthetic images of different hickness and noise levels, obtaining an edge detection with a maximal mean error lower than 16 percent of a pixel.

Direct estimation of the backward flow

[EN] The aim of this work is to propose a new method for estimating the backward flow directly from the optical flow. We assume that the optical flow has already been computed and we need to estimate the inverse mapping. This mapping is not bijective due to the presence of occlusions and disocclusions, therefore it is not possible to estimate the inverse function in the whole domain. Values in these regions has to be guessed from the available information. We propose an accurate algorithm to calculate the backward flow uniquely from the optical flow, using a simple relation. Occlusions are filled by selecting the maximum motion and disocclusions are filled with two different strategies: a min-fill strategy, which fills each disoccluded region with the minimum value around the region; and a restricted min-fill approach that selects the minimum value in a close neighborhood. In the experimental results, we show the accuracy of the method and compare the results using these two strategies.

Horn-schunck optical flow with a multi-scale strategy

[EN] The seminal work of Horn and Schunck [8] is the first variational method for optical flow estimation. It introduced a novel framework where the optical flow is computed as the solution of a minimization problem. From the assumption that pixel intensities do not change over time, the optical flow constraint equation is derived. This equation relates the optical flow with the derivatives of the image. There are infinitely many vector fields that satisfy the optical flow constraint, thus the problem is ill-posed. To overcome this problem, Horn and Schunck introduced an additional regularity condition that restricts the possible solutions. Their method minimizes both the optical flow constraint and the magnitude of the variations of the flow field, producing smooth vector fields. One of the limitations of this method is that, typically, it can only estimate small motions. In the presence of large displacements, this method fails when the gradient of the image is not smooth enough. In this work, we describe an implementation of the original Horn and Schunck method and also introduce a multi-scale strategy in order to deal with larger displacements. For this multi-scale strategy, we create a pyramidal structure of downsampled images and change the optical flow constraint equation with a nonlinear formulation. In order to tackle this nonlinear formula, we linearize it and solve the method iteratively in each scale. In this sense, there are two common approaches: one that computes the motion increment in the iterations, like in ; or the one we follow, that computes the full flow during the iterations, like in. The solutions are incrementally refined ower the scales. This pyramidal structure is a standard tool in many optical flow methods.

Contributions to underwater glider path planning

[ES] La Planificación de Rutas o Caminos es un disciplina de Robótica que trata la búsqueda de caminos factibles u óptimos. Para la mayoría de vehículos y entornos, no es un problema trivial y por tanto nos encontramos con un gran diversidad de algoritmos para resolverlo, no sólo en Robótica e Inteligencia Artificial, sino también como parte de la literatura de Optimización, con Métodos Numéricos y Algoritmos Bio-inspirados, como Algoritmos Genéticos y el Algoritmo de la Colonia de Hormigas. El caso particular de escenarios de costes variables es considerablemente difícil de abordar porque el entorno en el que se mueve el vehículo cambia con el tiempo. El presente trabajo de tesis estudia este problema y propone varias soluciones prácticas para aplicaciones de Robótica Submarina.

Entorno de desarrollo con software libre para aplicaciones goegráficas 3D

[ES] La superficie afectada por incendios en Gran Canaria y Tenerife en Agosto de 2007 (aproximadamente 35.060 hectáreas) fue similar a la quemada en los últimos 22 años en todo el Archipiélago Canario. Sin duda, en los momentos clave de incen-dios, cuando la prevención se ha visto desbordada, se impone una planificación y actuación en base a simulaciones predicti-vas que ayuden a minimizar los daños ocasionados. Los gestores virtuales por ordenador pretenden ser herramientas de ayu-da en este propósito. Se presenta un entorno de desarrollo robusto, funcional y flexible encaminado a crear aplicaciones geográficas 3D mul-ticapa centrado, en esta etapa de desarrollo, en la aplicación a un Gestor Virtual de Emergencias1 (Geviemer) con la capaci-dad de simulación y predicción del fuego en incendios forestales. Se ofrece una herramienta de utilidad para el análisis y la toma de decisiones en incendios en Canarias, con una visualización tridimensional que permite la interacción en tiempo real. El entorno, desarrollado con software libre y diseñado en base a una arquitectura por capas permite adaptarlo completa-mente a las necesidades del usuario, ofreciendo un marco abierto a la especialización en aplicaciones concretas. Se analizan en esta comunicación los pormenores del entorno, destacando las características del diseño del software y las particularida-des de Geviemer.

Aplicación para la gestión de emergencias en la comunidad canaria.

[ES] Canarias es una región muy sensible a los incendios forestales. Cuando surge un evento de este tipo, se impone una gestión adecuada, encaminada a minimizar los daños ocasionados y en definitiva a la rápida extinción del incendio. Sólo en Gran Canaria y Tenerife, la superficie afectada por incendios en el mes de Agosto de 2007 (aproximadamente 35.060 hectáreas) fue similar a la quemada en los últimos 22 años en todo el archipiélago canario. Recientemente, están emergiendo asistentes como los gestores virtuales en tiempo real, los cuales pretenden ser herramientas de ayuda en este tipo de sucesos. Se presenta en este trabajo un sistema informático para la gestión de emergencias en la comunidad canaria, en la actualidad en fase de pruebas en el Cabildo de La Palma. Si bien la aplicación está diseñada para cualquier tipo de emergencia, en el estado actual del proyecto se desarrolla el caso de la predicción y simulación de incendios forestales en las Islas. La aplicación desarrollada ha suscitado el interés de la Consejería de Medio Ambiente (Sección de Montes) de este Cabildo, la cual colabora activamente para poner en producción un sistema plenamente operativo.

Variational second order flow estimation for PIV sequences

[EN] We present in this paper a variational approach to accurately estimate simultaneously the velocity field and its derivatives directly from PIV image sequences. Our method differs from other techniques that have been presented in the literature in the fact that the energy minimization used to estimate the particles motion depends on a second order Taylor development of the flow. In this way, we are not only able to compute the motion vector field, but we also obtain an accurate estimation of their derivatives. Hence, we avoid the use of numerical schemes to compute the derivatives from the estimated flow that usually yield to numerical amplification of the inherent uncertainty on the estimated flow. The performance of our approach is illustrated with the estimation of the motion vector field and the vorticity on both synthetic and real PIV datasets.

CART application to image primitives tracking

[EN] [EN] In this paper we present a new method for image primitives tracking based on a CART (Classification and Regression Tree). Primitives tracking procedure uses lines and circles as primitives. We have applied the proposed method to sport event scenarios, specifically, soccer matches. We estimate CART parameters using a learning procedure based on RGB image channels. In order to illustrate its performance, it has been applied to real HD (High Definition) video sequences and some numerical experiments are shown. The quality of the primitives tracking with the decision tree is validated by the percentage error rates obtained and the comparison with other techniques as a morphological method. We also present applications of the proposed method to camera calibration and graphic object insertion in real video sequences.

Temporal constraints in large optical flow estimation

[EN] The aim of this work is to propose a model for computing the optical flow in a sequence of images. We introduce a new temporal regularizer that is suitable for large displacements. We propose to decouple the spatial and temporal regularizations to avoid an incongruous formulation. For the spatial regularization we use the Nagel-Enkelmann operator and a newly designed temporal regularization. Our model is based on an energy functional that yields a partial differential equation (PDE). This PDE is embedded into a multipyramidal strategy to recover large displacements. A gradient descent technique is applied at each scale to reach the minimum.

Wildfire prevention and management in a 3D virtual environment

[EN] This paper describes a wildfire forecasting application based on a 3D virtual environment and a fire simulation engine. A new open source framework is presented for the development of 3D graphics applications over large geographic areas offering high performance 3D visualization and powerful interaction tools for the Geographic Information Systems community. The application includes a remote module that allows simultaneous connection of several users for monitoring a real wildfire event. The user is enabled to simulate and visualize a wildfire spreading on the terrain under conditions of spatial information on topography and fuels along with weather and wind files.

Wildfire frecasting using an open source 3D multilayer geographical framework

[EN] This abstract describes the development of a wildfire forecasting plugin using Capaware. Capaware is designed as an easy to use open source framework to develop 3D graphics applications over large geographic areas offering high performance 3D visualization and powerful interaction tools for the Geographic Information Systems (GIS) community.

Detección y caracterización de estructuras de meso y submesoescala a partir de modelos de predicción oceánicos

[ES] El proyecto trata sobre la detección y caracterización de estructuras oceánicas de mesoescala, concretamente, los giros. Estas estructuras son muy importantes a la hora del estudio de numerosos procesos físicos, químicos y biológicos que suceden en el medio oceánico. Para ello, se han estudiado otros sistemas relacionados, se ha creado una aplicación con la que los usuarios puedan caracterizar giros de forma sencilla, y una serie de herramientas automáticas de detección de giros. Por último se han realizado una serie de pruebas y comparativas de las herramientas desarrolladas para demostrar su eficacia y que éstas cumplen todos los objetivos que se propusieron en el proyecto.