Traducción automática estadística: modelos de traducción basados en máxima entropía y algoritmos de búsqueda

Tesis en españolThis thesis is completely devoted to machine translation, a discipline which belongs to the fields of artificial intelligence and computational linguistics, and it is more specifically devoted to the statistical machine translation approach. The work presented here is based solely on the translation approach to Bayes' decision rule. Thus, this work can be classified as empiricist in contrast to a more rationalistic approach based on linguistic techniques. We can distinguish three main different ingredients within this approach to machine translation: a language model, a translation model, and a search decoding problem. The latter can be considered the sheer problem of machine translation. The first ingredient, the language model, is not treated here in full, mainly because it has been widely studied and used in the field of automatic speech recognition. Due to this, we only make use of the techniques already developed in language modelling and, more specifically, we use the well-known n-gram models. Nonetheless, because their relevance to the problem addressed in this thesis, we do introduce the basic and necessary concepts of language models. With respect to translation models, it must be said first that this work is based on single-word statistical translation models. We have introduced context-dependent lexicon models based on maximum entropy techniques. In particular, we have seen how to develop maximum entropy translation models, how to integrate them into the training algorithms of conventional translation models, and how to use them in order to improve the performance of statistical machine translation systems. Regarding the search decoding problem, we have proposed, designed, and studied several search algorithms following three classical problem solving paradigms. Those paradigms are: dynamic programming, the branch and bound approach, and the greedy algorithms approach. For all of them we have performed a detailed study concerning efficiency and translation quality. Additionally, a study of computational and empirical complexity has been done. This work has been supported by a large quantity of experiments, which were carried out on three well-known tasks in the field of machine translation: the tourist Spanish-English task (better known as EuTrans-I), the French-English Hansards task, and the German-English Verbmobil task

Semantic localization in the PCL library

The semantic localization problem in robotics consists in determining the place where a robot is located by means of semantic categories. The problem is usually addressed as a supervised classification process, where input data correspond to robot perceptions while classes to semantic categories, like kitchen or corridor. In this paper we propose a framework, implemented in the PCL library, which provides a set of valuable tools to easily develop and evaluate semantic localization systems. The implementation includes the generation of 3D global descriptors following a Bag-of-Words approach. This allows the generation of fixed-dimensionality descriptors from any type of keypoint detector and feature extractor combinations. The framework has been designed, structured and implemented to be easily extended with different keypoint detectors, feature extractors as well as classification models. The proposed framework has also been used to evaluate the performance of a set of already implemented descriptors, when used as input for a specific semantic localization system. The obtained results are discussed paying special attention to the internal parameters of the BoW descriptor generation process. Moreover, we also review the combination of some keypoint detectors with different 3D descriptor generation techniques.This work was supported by grant DPI2013-40534-R of the Ministerio de Economia y Competitividad of the Spanish Government, supported with Feder funds, and by Consejería de Educación, Cultura y Deportes of the JCCM regional government through project PPII-2014-015-P. Jesus Martínez-Gómez was also funded by the JCCM grant POST2014/8171

ViDRILO: The Visual and Depth Robot Indoor Localization with Objects information dataset

In this article we describe a semantic localization dataset for indoor environments named ViDRILO. The dataset provides five sequences of frames acquired with a mobile robot in two similar office buildings under different lighting conditions. Each frame consists of a point cloud representation of the scene and a perspective image. The frames in the dataset are annotated with the semantic category of the scene, but also with the presence or absence of a list of predefined objects appearing in the scene. In addition to the frames and annotations, the dataset is distributed with a set of tools for its use in both place classification and object recognition tasks. The large number of labeled frames in conjunction with the annotation scheme make this dataset different from existing ones. The ViDRILO dataset is released for use as a benchmark for different problems such as multimodal place classification and object recognition, 3D reconstruction or point cloud data compression.This work was supported by the Ministerio de Economia y Competitividad of the Spanish Government, and by Consejería de Educación, Cultura y Deportes of the JCCM regional government through project PPII-2014-015-P (grant number DPI2013-40534-R). Jesus Martínez-Gómez is also funded by the JCCM (grant number POST2014/8171)

Using genetic algorithms for real-time object detection

P. 1-12This article presents a new approach to mobile robot vision systems based on genetic algorithms. The major contribution of the proposal is the real-time adaptation of genetic algorithms, which are generally used offline. In order to achieve this goal, the execution time must be as short as possible. The scope of the System is the robotic football competition Robocup whitin the Standard Platform category. The system developed detects and estimates distance and orientation to key elements on a football field, such as the ball and goals. Different experiments have been carried out whitin an official Robocup environmentS

Computing Image Descriptors from Annotations Acquired from External Tools

Visual descriptors are widely used in several recognition and classification tasks in robotics. The main challenge for these tasks is to find a descriptor that could represent the image content without losing representative information of the image. Nowadays, there exists a wide range of visual descriptors computed with computer vision techniques and different pooling strategies. This paper proposes a novel way for building image descriptors using an external tool, namely: Clarifai. This is a remote web tool that allows to automatically describe an input image using semantic tags, and these tags are used to generate our descriptor. The descriptor generation procedure has been tested in the ViDRILO dataset, where it has been compared and merged with some well-known descriptors. Moreover, subset variable selection techniques have been evaluated. The experimental results show that our descriptor is competitive in classification tasks with the results obtained with other kind of descriptors.Visual descriptors are widely used in several recognition and classification tasks in robotics. The main challenge for these tasks is to find a descriptor that could represent the image content without losing representative information of the image. Nowadays, there exists a wide range of visual descriptors computed with computer vision techniques and different pooling strategies. This paper proposes a novel way for building image descriptors using an external tool, namely: Clarifai. This is a remote web tool that allows to automatically describe an input image using semantic tags, and these tags are used to generate our descriptor. The descriptor generation procedure has been tested in the ViDRILO dataset, where it has been compared and merged with some well-known descriptors. Moreover, subset variable selection techniques have been evaluated. The experimental results show that our descriptor is competitive in classification tasks with the results obtained with other kind of descriptors

LexToMap: lexical-based topological mapping

Any robot should be provided with a proper representation of its environment in order to perform navigation and other tasks. In addition to metrical approaches, topological mapping generates graph representations in which nodes and edges correspond to locations and transitions. In this article, we present LexToMap, a topological mapping procedure that relies on image annotations. These annotations, represented in this work by lexical labels, are obtained from pre-trained deep learning models, namely CNNs, and are used to estimate image similarities. Moreover, the lexical labels contribute to the descriptive capabilities of the topological maps. The proposal has been evaluated using the KTH-IDOL 2 data-set, which consists of image sequences acquired within an indoor environment under three different lighting conditions. The generality of the procedure as well as the descriptive capabilities of the generated maps validate the proposal.This work was supported by the Ministerio de Economia y Competitividad of the Spanish Government, supported with Feder funds, under grant DPI2013-40534-R and TIN2015-66972-C5-2-R; Consejería de Educación, Cultura y Deportes of the JCCM regional government under project PPII-2014- 015-P. José Carlos Rangel is also funded by the IFARHU of the Republic of Panamá under grant 8- 2014-166

Uso de algoritmos genéticos para detección de objetos en tiempo real

El artículo presenta un sistema de Visión para la detección de objetos mediante el uso de algoritmos genéticos. La principal aportación del mismo consiste en la adaptación al tiempo real de algoritmos generalmente utilizados offline. Para conseguir esto se necesita una ejecución eficiente que reduzca al máximo la complejidad del algoritmo. El ámbito de aplicación del sistema es el campeonato de fútbol robótico RoboCup, en concreto la categoría Standard Platform, y debe permitir detectar y estimar distancias a los objetos relevantes dentro de un estadio de fútbol. Se realizaron diferentes experimentos dentro de un campo oficial RoboCu

Una Herramienta para la estimación del esfuerzo del estudiante de grado en ingeniería informática

En el marco de las nuevas titulaciones de Grado en Ingeniería Informática, resulta muy conveniente establecer algún tipo de mecanismo que nos permita recoger información sobre la dedicación real de los estudiantes a nuestras asignaturas. A nivel de asignatura, esta información puede servir al profesorado para determinar el grado de acierto de su planificación temporal inicial. A un nivel más global, los datos recogidos proporcionan a los coordinadores de curso una idea de la carga total a la que está sometido el estudiante, y contribuyen a la identificación de posibles picos (o valles) de trabajo durante el cuatrimestre. En este trabajo se describe la puesta en marcha de un sistema, basado en encuestas, para el conocimiento del esfuerzo de los estudiantes de Grado en Ingeniería Informática de la Escuela Superior de Ingeniería Informática de Albacete. También se presentan y analizan algunos de los resultados obtenidos durante el curso académico 2012/13.SUMMARY -- In the framework of new degrees in Computer Science, it is desirable to establish some mechanism to let us collect some information about our students' commitment to our courses. On the subject level, this information may be useful for the teaching staff to determine the degree of success of this initial temporary planning. In a high level point of view, the data collected provide the course coordination with an idea of the total workload of students and it contributes to identify potential peaks (or valleys) of work throughout the semester. This work presents a surveybased system to obtain and register the efforts of our Computer Engineering students from the School of Computer Engineering of Albacete. It also introduces and discusses some of the results obtained during the academic year 2012/13

Experiencias en el desarrollo del Plan de Coordinación Docente del Grado en Ingeniería Informática

Una buena coordinación del equipo docente implicado en cualquier titulación es indispensable para la correcta consecución, por parte de los estudiantes, de las competencias específicas y transversales recogidas en su plan de estudios. Dos años después de la implantación, por inmersión, de la nueva titulación de Grado en Ingeniería Informática adaptada al Espacio Europeo de Educación Superior (EEES), compartimos en este trabajo nuestras experiencias y reflexiones en la puesta en marcha del Plan de Coordinación que había sido definido. En particular, concretamos las acciones de coordinación llevadas a cabo, haciendo hincapié en las herramientas de las que nos hemos servido. También identificamos las fortalezas y debilidades detectadas, así como las dificultades encontradas, proponiendo líneas de actuación futuras.A good coordination of the teaching staff involved in a degree is essential for the achievement by students of the transversal and generic skills considered in the corresponding syllabus. Two years after the complete implantation of the new degree in Computing, which has been adapted to the European Higher Education Area (EHEA), in this paper we detail our experiences and thoughts on the implementation of the Coordination Plan initially proposed. In particular, we focus on the coordination tasks carried out and the tools that we have used. We also identify the strengths and weaknesses observed and the handicaps found. Finally, we propose some lines of future work

XII Workshop of Physical Agents (WAF'2011)

The Workshop of Physical Agents intends to be a forum for information and experience exchange in different areas regarding the concept of agent in physical environments, especially applied to the control and coordination of autonomous systems: robots, mobile robots, industrial processes or complex systems. This special issue is devoted to the selected papers presented in the WAF’11 that took place in Albacete (SPAIN) from 5th to 6th of September