Catálogo de publicaciones - libros

A 3D virtual model of the human lower extremity has been developed for the purpose of examining how the neuromuscular system controls the muscles and generates the desired movement. Our virtual knee currently incorporates the major muscles spanning the knee joint and it is used to estimate the knee joint moment. Beside that we developed a graphical interface that allows the user to visualize the skeletal geometry and the movements imparted to it. The purpose of this paper is to describe the design objectives and the implementation of our EMG-driven virtual knee. We finally compared the virtual knee behavior with the torque performed by the test subject in order to obtain a qualitative validation of our model. Within the next future our aim is to develop a real-time EMG-driven exoskeleton for knee rehabilitation.

In this paper we investigate the interaction between emotional and non-emotional aspects of persuasion dialogues, from the viewpoint of both the system (the Persuader), when reasoning on the persuasion attempt, and the user (the Receiver), when reacting to it. We are working on an Embodied Conversational Agent (ECA) which applies natural argumentation techniques to persuade users to improve their behaviour in the healthy eating domain. The ECA observes the user’s attitude during the dialogue, so as to select an appropriate persuasion strategy or to respond intelligently to user’s reactions to suggestions received. We grounded our work on the analysis of two corpora: a corpus of ‘natural’ persuasion examples and a corpus of user’s reactions to persuasion attempts.

A paradigm for music expression understanding based on a joint semantic space, described by both affective and sensorial adjectives, is presented. Machine learning techniques were employed to select and validate relevant low level features, and an interpretation of the clustered organization based on action and physical analogy is proposed.

Game generation systems perform automated, intelligent design of games ( videogames, boardgames), reasoning about both the abstract rule system of the game and the visual realization of these rules. Although, as an instance of the problem of creative design, game generation shares some common research themes with other creative AI systems such as story and art generators, game generation extends such work by having to reason about artifacts. Like AI work on creativity in other domains, work on game generation sheds light on the human game design process, offering opportunities to make explicit the tacit knowledge involved in game design and test game design theories. Finally, game generation enables new game genres which are radically customized to specific players or situations; notable examples are cell phone games customized for particular users and newsgames providing commentary on current events. We describe an approach to formalizing game mechanics and generating games using those mechanics, using WordNet and ConceptNet to assist in performing common-sense reasoning about game verbs and nouns. Finally, we demonstrate and describe in detail a prototype that designs micro-games in the style of Nintendo’s series.

We have recently presented , an algorithm that can be used for speeding up the evaluation of Supervised Sequential Learning (SSL) classifiers. provides impressive time performance gain over the state-of-art Viterbi algorithm when applied to the tonal harmony analysis task. Along with interesting computational features, the algorithm reveals some properties that are of some interest to Cognitive Science and Computer Music. To explore the question whether and to what extent the implemented system is suitable for cognitive modeling, we first elaborate about its design principles, and then assess the quality of the analyses produced. A threefold experimentation reviews the learned weights, the classification errors, and the search space in comparison to the actual problem space; data about these points are reported and discussed.

An advertising message induces in the recipient a positive (or negative) attitude toward the subject to advertise, for example through the evocation of a appropriate emotion. This paper is about the use of text processing techniques for proposing solutions to advertising professionals, opening up the way to a full automatization of the whole process. The system has two steps: (i) the creative variation of familiar expressions, taking into account the affective content of the produced text, (ii) the automatic animation (semantically consistent with the affective text content) of the resulting headline, using kinetic typography techniques.

Image digital archives of illuminated manuscripts can become a useful tool for researchers in different disciplines. To this aim, it is proposed to provide them with tools for annotating images to disclose hidden relationships between illustrations belonging to different works. Relationships can be modeled as typed links, which induce an hypertext over the archive. In this paper we present a formal model for annotations, which is the basis to build methods for automatically processing existing relationships among link types and exploiting the properties of the graph which models the hypertext.

In this paper, an unsupervised image classification technique combining features from different media levels is proposed. In particular geometrical models of visual features are here integrated with textual descriptions derived through Information Extraction processes from Web pages. While the higher expressivity of the combined individual descriptions increases the complexity of the adopted clustering algorithms, methods for dimensionality reduction (i.e. LSA) are applied effectively. The evaluation on an image classification task confirms that the proposed Web mining model outperforms other methods acting on the individual levels for cost-effective annotation.

We present our approach, integrating imaging and vision, for content-aware enhancement and processing of digital photographs. The overall quality of images is improved by a modular procedure automatically driven by the image class and content.

A Multimedia Surveillance System (MSS) is considered for automatically retrieving semantic content from complex outdoor scenes, involving both human behavior and traffic domains. To characterize the dynamic information attached to detected objects, we consider a deterministic modeling of spatio-temporal features based on abstraction processes towards fuzzy logic formalism. A situational analysis over conceptualized information will not only allow us to describe human actions within a scene, but also to suggest possible interpretations of the behaviors perceived, such as situations involving thefts or dangers of running over. Towards this end, the different levels of semantic knowledge implied throughout the process are also classified into a proposed taxonomy.