Experiences with free and open courses using on-line multimedia resources

This paper analyzes the learning experiences and opinions obtained from a group of undergraduate students in their interaction with several on-line multimedia resources included in a free on-line course about Computer Networks. These new educational resources employed are based on the Web2.0 approach such as blogs, videos and virtual labs which have been added in a web-site for distance self-learning.

Synchronous collaboration of virtual and remote laboratories

Virtual and remote laboratories(VRLs) are e-learning resources which enhance the accessibility of experimental setups providing a distance teaching framework which meets the student's hands-on learning needs. In addition, online collaborative communication represents a practical and a constructivist method to transmit the knowledge and experience from the teacher to students, overcoming physical distance and isolation. Thus, the integration of learning environments in the form of VRLs inside collaborative learning spaces is strongly desired. Considering these facts, the authors of this document present an original approach which enables user to share practical experiences while they work collaboratively through the Internet. This practical experimentation is based on VRLs, which have been integrated inside a synchronous collaborative e-learning framework. This article describes the main features of this system and its successful application for science and engineering subjects.

Detección automática con snakes y representación 3D sobre imágenes cerebrales

Comunicación presentada en la VI Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA'95), Alicante, 15-17 noviembre 1995.

Deformable templates for plaque thickness estimation of intravascular ultrasound sequences

Comunicación presentada en el VII Symposium Nacional de Reconocimiento de Formas y Análisis de Imágenes, SNRFAI, Barcelona, abril 1997.

Snakes based tracking and texture analysis of microscopic images

Comunicación presentada en el VII Symposium Nacional de Reconocimiento de Formas y Análisis de Imágenes, SNRFAI, Barcelona, abril 1997.

Plantillas deformables espacio-temporales para el tracking y reconocimiento gestual

Comunicación presentada en la VII Conferencia de la Asociación Española para la Inteligencia Artificial, CAEPIA, Málaga, 12-14 noviembre, 1997.

Estimación del movimiento coherente: computación evolutiva como alternativa al annealing determinista

Comunicación presentada en SCETA, Seminario Sobre Computación Evolutiva, celebrado en la VII Conferencia de la Asociación Española para la Inteligencia Artificial, CAEPIA, Málaga, 12-14 noviembre 1997.

A competition-based deformable template for junction extraction

Comunicación presentada en el VIII Simposium Nacional de Reconocimiento de Formas y Análisis de Imágenes, Bilbao, mayo 1999.

3D model based map building

Comunicación presentada en el IX Workshop de Agentes Físicos (WAF'2008), Vigo, 11-12 septiembre 2008.

Topological SLAM using a graph-matching based method on omnidirectional images

Comunicación presentada en el XI Workshop of Physical Agents, Valencia, 9-10 septiembre 2010.

Comparativa de detectores de características visuales y su aplicación al SLAM

Comunicación presentada en el X Workshop of Physical Agents, Cáceres, 10-11 septiembre 2009.

Large scale SLAM with visual features

Comunicación presentada en el X Workshop of Physical Agents, Cáceres, 10-11 septiembre 2009.

Deformable templates for tracking and analysis of intravascular ultrasound sequences

Deformable Template models are first applied to track the inner wall of coronary arteries in intravascular ultrasound sequences, mainly in the assistance to angioplasty surgery. A circular template is used for initializing an elliptical deformable model to track wall deformation when inflating a balloon placed at the tip of the catheter. We define a new energy function for driving the behavior of the template and we test its robustness both in real and synthetic images. Finally we introduce a framework for learning and recognizing spatio-temporal geometric constraints based on Principal Component Analysis (eigenconstraints).

A combined probabilistic framework for learning gestures and actions

In this paper we introduce a probabilistic approach to support visual supervision and gesture recognition. Task knowledge is both of geometric and visual nature and it is encoded in parametric eigenspaces. Learning processes for compute modal subspaces (eigenspaces) are the core of tracking and recognition of gestures and tasks. We describe the overall architecture of the system and detail learning processes and gesture design. Finally we show experimental results of tracking and recognition in block-world like assembling tasks and in general human gestures.

Constellations and the unsupervised learning of graphs

In this paper, we propose a novel method for the unsupervised clustering of graphs in the context of the constellation approach to object recognition. Such method is an EM central clustering algorithm which builds prototypical graphs on the basis of fast matching with graph transformations. Our experiments, both with random graphs and in realistic situations (visual localization), show that our prototypes improve the set median graphs and also the prototypes derived from our previous incremental method. We also discuss how the method scales with a growing number of images.