Luis Alvarez

Cooper Cone, Michael Owen, Luis Alvarez et al.

The proliferation of unmanned aircraft systems (UAS) has caused airspace regulation authorities to examine the interoperability of these aircraft with collision avoidance systems initially designed for large transport category aircraft. Limitations in the currently mandated TCAS led the Federal Aviation Administration to commission the development of a new solution, the Airborne Collision Avoidance System X (ACAS X), designed to enable a collision avoidance capability for multiple aircraft platforms, including UAS. While prior research explored using deep reinforcement learning algorithms (DRL) for collision avoidance, DRL did not perform as well as existing solutions. This work explores the benefits of using a DRL collision avoidance system whose parameters are tuned using a surrogate optimizer. We show the use of a surrogate optimizer leads to DRL approach that can increase safety and operational viability and support future capability development for UAS collision avoidance.

Luis Alvarez, Jean-Michel Morel

In this paper, we propose an active contour model for silhouette vectorization using cubic Bézier curves. Among the end points of the Bézier curves, we distinguish between corner and regular points where the orientation of the tangent vector is prescribed. By minimizing the distance of the Bézier curves to the silhouette boundary, the active contour model optimizes the location of the Bézier curves end points, the orientation of the tangent vectors in the regular points, and the estimation of the Bézier curve parameters. This active contour model can use the silhouette vectorization obtained by any method as an initial guess. The proposed method significantly reduces the average distance between the silhouette boundary and its vectorization obtained by the world-class graphic software Inkscape, Adobe Illustrator, and a curvature-based vectorization method, which we introduce for comparison. Our method also allows us to impose additional regularity on the Bézier curves by reducing their lengths.

Luis Alvarez, Pablo G. Tahoces, Emilio Macías-Conde

In this paper we revisit some classic board games like Pachisi or the Game of Gosse. The main contribution of the paper is to design and add some functionalities to the games in order to transform them in serious games, that is, in games with learning and educational purposes. To do that, at the beginning of the game, players choose one or several topics and during the game, players have to anwers questions on these topics in order to move their markers. We choose classic board games because a lot of people are familiar with them so it is very easy to start to play without wasting time learning game rules and, we think that this is an important element to make the game more attractive to people. To enlarge the number of potential users we have implement the games just using html and javascript and the games can be used in any web browser, in any computer (including tablets) , in any computer arquitecture (Windows, Mac, Linux) and no internet/server conexion is required. Associated software is distributed under Creative Commons Attribution-NonCommercial-ShareAlike 3.0 licence and can be obtained at http://www.ctim.es/SeriousGames

Luis Gomez, Luis Alvarez, Luis Mazorra et al.

We propose a new method for PolSAR (Polarimetric Synthetic Aperture Radar) imagery classification based on stochastic distances in the space of random matrices obeying complex Wishart distributions. Given a collection of prototypes $\{Z_m\}_{m=1}^M$ and a stochastic distance $d(.,.)$, we classify any random matrix $X$ using two criteria in an iterative setup. Firstly, we associate $X$ to the class which minimizes the weighted stochastic distance $w_md(X,Z_m)$, where the positive weights $w_m$ are computed to maximize the class discrimination power. Secondly, we improve the result by embedding the classification problem into a diffusion-reaction partial differential system where the diffusion term smooths the patches within the image, and the reaction term tends to move the pixel values towards the closest class prototype. In particular, the method inherits the benefits of speckle reduction by diffusion-like methods. Results on synthetic and real PolSAR data show the performance of the method.