X Workshop of Physical Agents (WAF'2009)

The Workshop of Physical Agents intends to be a forum for information and experience exchange in different areas regarding the concept of embodied agents, especially applied to the control and coordination of autonomous system: robots, mobile robots, industrial processes or complex system. This special issue is devoted to the selected papers presented at the WAF09 that took place from September 10th to 11th in the city of Cáceres (Spain)

Herramientas de apoyo en la docencia de la inteligencia artificial

La asignatura de Inteligencia Artificial se imparte en la Universidad de Extremadura desde el curso académico 95-96. Se trata de una materia troncal de segundo ciclo, con un alumnado muy heterogéneo y con un perfil amplio. El temario se ha diseñado para abarcar unos conocimientos generales que sirvan de base a todos los alumnos. Se ha dividido en tres grandes apartados: Representación del conocimiento, Resolución de problemas y Adquisición de conocimiento. Asimismo, se proponen tres prácticas complementarias, cuyo principal objetivo es dar a conocer los dos lenguajes típicos de la IA: Prolog y Lisp. Como apoyo en la docencia, se presentan tres herramientas que tratan de facilitar la comprensión de otros tantos temas de la materia. La primera es un simulador del algoritmo A*, que permite estudiar el comportamiento del mismo resolviendo el conocido problema del 8-puzle. El segundo desarrolla el sistema Strips, generando planes para un mundo de bloques ideal. Finalmente, el tercero es un simulador de una red neuronal del tipo backpropagation, que puede ser entrenada para diferentes patrones. Todas ellas han sido desarrolladas por alumnos de la Escuela en diferentes proyectos fin de carrera

A Spiking Neural Model of HT3D for Corner Detection

Obtaining good quality image features is of remarkable importance for most computer vision tasks. It has been demonstrated that the first layers of the human visual cortex are devoted to feature detection. The need for these features has made line, segment, and corner detection one of the most studied topics in computer vision. HT3D is a recent variant of the Hough transform for the combined detection of corners and line segments in images. It uses a 3D parameter space that enables the detection of segments instead of whole lines. This space also encloses canonical configurations of image corners, transforming corner detection into a pattern search problem. Spiking neural networks have previously been proposed for multiple image processing tasks, including corner and line detection using the Hough transform. Following these ideas, this paper presents and describes in detail a model to implement HT3D as a Spiking Neural Network for corner detection. The results obtained from a thorough testing of its implementation using real images evince the correctness of the Spiking Neural Network HT3D implementation. Such results are comparable to those obtained with the regular HT3D implementation, which are turn superior to other corner detection algorithms

A spiking neural model of HT3D for corner detection

La obtención de características de imagen de buena calidad es de notable importancia para la mayoría de las tareas de visión artificial. Se ha demostrado que las primeras capas de la corteza visual humana están dedicadas a la detección de características. La necesidad de estas características ha hecho que la detección de líneas, segmentos y esquinas sea uno de los temas más estudiados en la visión por computador. El HT3D es una variante reciente de la transformación Hough para la detección combinada de esquinas y segmentos de línea en imágenes. Utiliza un espacio de parámetros 3D que permite la detección de segmentos en lugar de líneas enteras. Este espacio también encierra configuraciones canónicas de las esquinas de la imagen, transformando la detección de esquinas en un problema de búsqueda de patrones. Las redes neuronales de picos (SNN) se han propuesto anteriormente para múltiples tareas de procesamiento de imágenes, incluyendo la detección de esquinas y líneas usando la transformación Hough. Siguiendo estas ideas, este documento presenta y describe en detalle un modelo para implementar el HT3D como una Red Neural de Picos (Spiking Neural Network) para la detección de esquinas. Los resultados obtenidos a partir de pruebas exhaustivas de su implementación utilizando imágenes reales evidencian la corrección de la implementación de la Red Neural Spiking HT3D. Tales resultados son comparables a los obtenidos con la implementación regular del HT3D, que a su vez son superiores a otros algoritmos de detección de esquinas.Obtaining good quality image features is of remarkable importance for most computer vision tasks. It has been demonstrated that the first layers of the human visual cortex are devoted to feature detection. The need for these features has made line, segment, and corner detection one of the most studied topics in computer vision. HT3D is a recent variant of the Hough transform for the combined detection of corners and line segments in images. It uses a 3D parameter space that enables the detection of segments instead of whole lines. This space also encloses canonical configurations of image corners, transforming corner detection into a pattern search problem. Spiking neural networks (SNN) have previously been proposed for multiple image processing tasks, including corner and line detection using the Hough transform. Following these ideas, this paper presents and describes in detail a model to implement HT3D as a Spiking Neural Network for corner detection. The results obtained froma thorough testing of its implementation using real images evince the correctness of the Spiking Neural Network HT3D implementation. Such results are comparable to those obtained with the regular HT3D implementation, which are in turn superior to other corner detection algorithms.• Unión Europea. Proyecto Interreg. Beca 0043_EUROAGE_4_E • Gobierno de España. Beca TIN2015-65686-C5-5-R • Junta de Extremadura. Beca GR15120 e IB16090peerReviewe

Multi-person 3D pose estimation from unlabelled data

Its numerous applications make multi-human 3D pose estimation a remarkably impactful area of research. Nevertheless, it presents several challenges, especially when approached using multiple views and regular RGB cameras as the only input. First, each person must be uniquely identified in the different views. Secondly, it must be robust to noise, partial occlusions, and views where a person may not be detected. Thirdly, many pose estimation approaches rely on environment-specific annotated datasets that are frequently prohibitively expensive and/or require specialised hardware. Specifically, this is the first multi-camera, multi-person data-driven approach that does not require an annotated dataset. In this work, we address these three challenges with the help of self-supervised learning. In particular, we present a three-staged pipeline and a rigorous evaluation providing evidence that our approach performs faster than other state-of-the-art algorithms, with comparable accuracy, and most importantly, does not require annotated datasets. The pipeline is composed of a 2D skeleton detection step, followed by a Graph Neural Network to estimate cross-view correspondences of the people in the scenario, and a Multi-Layer Perceptron that transforms the 2D information into 3D pose estimations. Our proposal comprises the last two steps, and it is compatible with any 2D skeleton detector as input. These two models are trained in a self-supervised manner, thus avoiding the need for datasets annotated with 3D ground-truth poses

PechaKuchaPolitec: trabajos de clase en 6:40 para todos

En este trabajo se presenta una experiencia de divulgación técnica abierta al público en la que los estudiantes de titulaciones TIC presentan trabajos de clase en formato PechaKucha. El principal objetivo de esta actividad ha sido que los estudiantes puedan exponer a un público amplio los interesantes trabajos realizados en diferentes asignaturas, dando así a conocer estas asignaturas a futuros estudiantes y poniendo en práctica su competencia como oradores. Los autores consideran que la experiencia puede ser útil como actividad extracurricular de divulgación y que resulta interesante y motivadora para estudiantes y profesores.In this paper, it is presented an experience in which Information and Communication Technologies (ICT) Degree students take part in a PechaKucha event. The main objective of this activity was to give the students the opportunity of presenting interesting pieces of work carried out in differents subjects to a broad public, introducing these courses to future students and enabling the speakers the development of generic skills. The authors believe that the experience can be useful as a extracurricular activity of dissemination and it is also interesting and motivating for both students and teachers.Trabajo financiado parcialmente por la Consejería de Empleo, Empresa e Innovación - Gobierno de Extremadura (GR10129) y el Fondo Europeo para el Desarrollo Regional (FEDER

A Survey on Socially Aware Robot Navigation: Taxonomy and Future Challenges

Socially aware robot navigation is gaining popularity with the increase in delivery and assistive robots. The research is further fueled by a need for socially aware navigation skills in autonomous vehicles to move safely and appropriately in spaces shared with humans. Although most of these are ground robots, drones are also entering the field. In this paper, we present a literature survey of the works on socially aware robot navigation in the past 10 years. We propose four different faceted taxonomies to navigate the literature and examine the field from four different perspectives. Through the taxonomic review, we discuss the current research directions and the extending scope of applications in various domains. Further, we put forward a list of current research opportunities and present a discussion on possible future challenges that are likely to emerge in the field

Experiencia de coordinación con el método de la clase al revés en grados de Ingeniería Informática

En este trabajo se presenta una experiencia de implantación progresiva de la metodología de clase al revés en los dos primeros cursos comunes a dos grados de Ingeniería Informática en la Escuela Politécnica de la Universidad de Extremadura. A lo largo de los dos años que ha durado la experiencia, vertebrada con dos proyectos de innovación docente, han participado 13 asignaturas y 22 profesores de distintas áreas de conocimiento. El principal objetivo de este trabajo es explicar cómo se ha implantado esta experiencia para afrontar el reto de coordinación que supone involucrar a varias asignaturas con profesores con distintos niveles de conocimiento y aplicación de la clase al revés en sus asignaturas. La colaboración entre el profesorado ha sido fundamental para el aprendizaje y para el desarrollo de materiales y actividades adecuados para cada asignatura. Una buena ejecución de estos proyectos debería llevar a que la metodología sobreviva en las aulas más allá de la finalización de los proyectos docentes. Así, otra de las contribuciones del trabajo es medir el impacto que ha tenido esta metodología dos cursos después de la finalización de los proyectos. Además, se presentarán las lecciones aprendidas y que pueden ayudar a poner en marcha proyectos similares donde intervienen muchos profesores y asignaturas.In this paper we present an experience of progressive implementation of the flipped classroom methodology. We introduced changes in the two first common courses of two Degrees in Computer Science at Polytechnic School of University of Extremadura. The experience lasted for two years and it was vertebrated over two teaching innovation projects, involving 13 subjects and 22 teachers from different fields of knowledge. The main objective of this work is to explain how this experience was implemented to face the coordination challenge that arise when involving several subjects, and teachers with different levels of knowledge and application of the flipped classroom. Collaboration among teachers was essential for learning and developing appropriate materials and activities. A good execution of these projects should make the methodology survives in classrooms beyond completion of the teaching projects. So, another contribution of the work is to measure the impact of the methodology two courses after the completion of the projects. In addition, we enumerate some lessons learned willing to help similar projects, where many teachers and subjects are involved

A variant of the Hough Transform for the combined detection of corners, segments, and polylines

The Hough Transform (HT) is an effective and popular technique for detecting image features such as lines and curves. From its standard form, numerous variants have emerged with the objective, in many cases, of extending the kind of image features that could be detected. Particularly, corner and line segment detection using HT has been separately addressed by several approaches. To deal with the combined detection of both image features (corners and segments), this paper presents a new variant of the Hough Transform. The proposed method provides an accurate detection of segment endpoints, even if they do not correspond to intersection points between line segments. Segments are detected from their endpoints, producing not only a set of isolated segments but also a collection of polylines. This provides a direct representation of the polygonal contours of the image despite imperfections in the input data such as missing or noisy feature points. It is also shown how this proposal can be extended to detect predefined polygonal shapes. The paper describes in detail every stage of the proposed method and includes experimental results obtained from real images showing the benefits of the proposal in comparison with other approaches

X Workshop of Physical Agents (WAF'2009)

The Workshop of Physical Agents intends to be a forum for information and experience exchange in different areas regarding the concept of embodied agents, especially applied to the control and coordination of autonomous system: robots, mobile robots, industrial processes or complex system. This special issue is devoted to the selected papers presented at the WAF09 that took place from September 10th to 11th in the city of Cáceres (Spain)