Scene di violenza, esperienze emotive e condotte aggressive

The aim of this research is to estimate the impact of violent film excerpts on university students (30 f, 30 m) in two different sequences, a “justified” violent scene followed by an “unjustified” one, or vice versa, as follows: 1) before-after sequences, using Aggressive behaviour I-R Questionnaire, Self Depression Scale and ASQ-IPAT Anxiety SCALE; 2) after every excerpt, using a self-report to evaluate the intensity and hedonic tone of emotions and the violence justification level. Emotion regulation processes (suppression, reappraisal, self-efficacy) were considered. In contrast with the “unjustified” violent scene, during the “justified” one, the justification level was higher; intensity and unpleasantness of negative emotions were lower. Anxiety (total and latent) and rumination diminished after both types of sequences. Rumination decreases less after the JV-UV sequence than after the UV-JV sequence. Self-efficacy in controlling negative emotions reduced rumination, whereas suppression reduced irritability. Reappraisal, self-efficacy in positive emotion expression and perceived emphatic selfefficacy did not have any effects.

Reconstruction from image correspondences

A single picture provides a largely incomplete representation of the scene one is looking at. Usually it reproduces only a limited spatial portion of the scene according to the standpoint and the viewing angle, besides it contains only instantaneous information. Thus very little can be understood on the geometrical structure of the scene, the position and orientation of the observer with respect to it remaining also hard to guess. When multiple views, taken from different positions in space and time, observe the same scene, then a much deeper knowledge is potentially achievable. Understanding inter-views relations enables construction of a collective representation by fusing the information contained in every single image. Visual reconstruction methods confront with the formidable, and still unanswered, challenge of delivering a comprehensive representation of structure, motion and appearance of a scene from visual information. Multi-view visual reconstruction deals with the inference of relations among multiple views and the exploitation of revealed connections to attain the best possible representation. This thesis investigates novel methods and applications in the field of visual reconstruction from multiple views. Three main threads of research have been pursued: dense geometric reconstruction, camera pose reconstruction, sparse geometric reconstruction of deformable surfaces. Dense geometric reconstruction aims at delivering the appearance of a scene at every single point. The construction of a large panoramic image from a set of traditional pictures has been extensively studied in the context of image mosaicing techniques. An original algorithm for sequential registration suitable for real-time applications has been conceived. The integration of the algorithm into a visual surveillance system has lead to robust and efficient motion detection with Pan-Tilt-Zoom cameras. Moreover, an evaluation methodology for quantitatively assessing and comparing image mosaicing algorithms has been devised and made available to the community. Camera pose reconstruction deals with the recovery of the camera trajectory across an image sequence. A novel mosaic-based pose reconstruction algorithm has been conceived that exploit image-mosaics and traditional pose estimation algorithms to deliver more accurate estimates. An innovative markerless vision-based human-machine interface has also been proposed, so as to allow a user to interact with a gaming applications by moving a hand held consumer grade camera in unstructured environments. Finally, sparse geometric reconstruction refers to the computation of the coarse geometry of an object at few preset points. In this thesis, an innovative shape reconstruction algorithm for deformable objects has been designed. A cooperation with the Solar Impulse project allowed to deploy the algorithm in a very challenging real-world scenario, i.e. the accurate measurements of airplane wings deformations.

Emotional engagement and orienting: the effects of picture size on affective response

For their survival, humans and animals can rely on motivational systems which are specialized in assessing the valence and imminence of dangers and appetitive cues. The Orienting Response (OR) is a fundamental response pattern that an organism executes whenever a novel or significant stimulus is detected, and has been shown to be consistently modulated by the affective value of a stimulus. However, detecting threatening stimuli and appetitive affordances while they are far away compared to when they are within reach constitutes an obvious evolutionary advantage. Building on the linear relationship between stimulus distance and retinal size, the present research was aimed at investigating the extent to which emotional modulation of distinct processes (action preparation, attentional capture, and subjective emotional state) is affected when reducing the retinal size of a picture. Studies 1-3 examined the effects of picture size on emotional response. Subjective feeling of engagement, as well as sympathetic activation, were modulated by picture size, suggesting that action preparation and subjective experience reflect the combined effects of detecting an arousing stimulus and assessing its imminence. On the other hand, physiological responses which are thought to reflect the amount of attentional resources invested in stimulus processing did not vary with picture size. Studies 4-6 were conducted to substantiate and extend the results of studies 1-3. In particular, it was noted that a decrease in picture size is associated with a loss in the low spatial frequencies of a picture, which might confound the interpretation of the results of studies 1-3. Therefore, emotional and neutral images which were either low-pass filtered or reduced in size were presented, and affective responses were measured. Most effects which were observed when manipulating image size were replicated by blurring pictures. However, pictures depicting highly arousing unpleasant contents were associated with a more pronounced decrease in affective modulation when pictures were reduced in size compared to when they were blurred. The present results provide important information for the study of processes involved in picture perception and in the genesis and expression of an emotional response. In particular, the availability of high spatial frequencies might affect the degree of activation of an internal representation of an affectively charged scene, and might modulate subjective emotional state and preparation for action. Moreover, the manipulation of stimulus imminence revealed important effects of stimulus engagement on specific components of the emotional response, and the implications of the present data for some models of emotions have been discussed. In particular, within the framework of a staged model of emotional response, the tactic and strategic role of response preparation and attention allocation to stimuli varying in engaging power has been discussed, considering the adaptive advantages that each might represent in an evolutionary view. Finally, the identification of perceptual parameters that allow affective processing to be carried out has important methodological applications in future studies examining emotional response in basic research or clinical contexts.

Algorithms for on-line image registration from multiple views

Images of a scene, static or dynamic, are generally acquired at different epochs from different viewpoints. They potentially gather information about the whole scene and its relative motion with respect to the acquisition device. Data from different (in the spatial or temporal domain) visual sources can be fused together to provide a unique consistent representation of the whole scene, even recovering the third dimension, permitting a more complete understanding of the scene content. Moreover, the pose of the acquisition device can be achieved by estimating the relative motion parameters linking different views, thus providing localization information for automatic guidance purposes. Image registration is based on the use of pattern recognition techniques to match among corresponding parts of different views of the acquired scene. Depending on hypotheses or prior information about the sensor model, the motion model and/or the scene model, this information can be used to estimate global or local geometrical mapping functions between different images or different parts of them. These mapping functions contain relative motion parameters between the scene and the sensor(s) and can be used to integrate accordingly informations coming from the different sources to build a wider or even augmented representation of the scene. Accordingly, for their scene reconstruction and pose estimation capabilities, nowadays image registration techniques from multiple views are increasingly stirring up the interest of the scientific and industrial community. Depending on the applicative domain, accuracy, robustness, and computational payload of the algorithms represent important issues to be addressed and generally a trade-off among them has to be reached. Moreover, on-line performance is desirable in order to guarantee the direct interaction of the vision device with human actors or control systems. This thesis follows a general research approach to cope with these issues, almost independently from the scene content, under the constraint of rigid motions. This approach has been motivated by the portability to very different domains as a very desirable property to achieve. A general image registration approach suitable for on-line applications has been devised and assessed through two challenging case studies in different applicative domains. The first case study regards scene reconstruction through on-line mosaicing of optical microscopy cell images acquired with non automated equipment, while moving manually the microscope holder. By registering the images the field of view of the microscope can be widened, preserving the resolution while reconstructing the whole cell culture and permitting the microscopist to interactively explore the cell culture. In the second case study, the registration of terrestrial satellite images acquired by a camera integral with the satellite is utilized to estimate its three-dimensional orientation from visual data, for automatic guidance purposes. Critical aspects of these applications are emphasized and the choices adopted are motivated accordingly. Results are discussed in view of promising future developments.

A moment symbolic representation of Lévy processes with applications

By using a symbolic method, known in the literature as the classical umbral calculus, a symbolic representation of Lévy processes is given and a new family of time-space harmonic polynomials with respect to such processes, which includes and generalizes the exponential complete Bell polynomials, is introduced. The usefulness of time-space harmonic polynomials with respect to Lévy processes is that it is a martingale the stochastic process obtained by replacing the indeterminate x of the polynomials with a Lévy process, whereas the Lévy process does not necessarily have this property. Therefore to find such polynomials could be particularly meaningful for applications. This new family includes Hermite polynomials, time-space harmonic with respect to Brownian motion, Poisson-Charlier polynomials with respect to Poisson processes, Laguerre and actuarial polynomials with respect to Gamma processes , Meixner polynomials of the first kind with respect to Pascal processes, Euler, Bernoulli, Krawtchuk, and pseudo-Narumi polynomials with respect to suitable random walks. The role played by cumulants is stressed and brought to the light, either in the symbolic representation of Lévy processes and their infinite divisibility property, either in the generalization, via umbral Kailath-Segall formula, of the well-known formulae giving elementary symmetric polynomials in terms of power sum symmetric polynomials. The expression of the family of time-space harmonic polynomials here introduced has some connections with the so-called moment representation of various families of multivariate polynomials. Such moment representation has been studied here for the first time in connection with the time-space harmonic property with respect to suitable symbolic multivariate Lévy processes. In particular, multivariate Hermite polynomials and their properties have been studied in connection with a symbolic version of the multivariate Brownian motion, while multivariate Bernoulli and Euler polynomials are represented as powers of multivariate polynomials which are time-space harmonic with respect to suitable multivariate Lévy processes.

The spatial representation of time

Numerosi studi mostrano che gli intervalli temporali sono rappresentati attraverso un codice spaziale che si estende da sinistra verso destra, dove gli intervalli brevi sono rappresentati a sinistra rispetto a quelli lunghi. Inoltre tale disposizione spaziale del tempo può essere influenzata dalla manipolazione dell’attenzione-spaziale. La presente tesi si inserisce nel dibattito attuale sulla relazione tra rappresentazione spaziale del tempo e attenzione-spaziale attraverso l’uso di una tecnica che modula l’attenzione-spaziale, ovvero, l’Adattamento Prismatico (AP). La prima parte è dedicata ai meccanismi sottostanti tale relazione. Abbiamo mostrato che spostando l’attenzione-spaziale con AP, verso un lato dello spazio, si ottiene una distorsione della rappresentazione di intervalli temporali, in accordo con il lato dello spostamento attenzionale. Questo avviene sia con stimoli visivi, sia con stimoli uditivi, nonostante la modalità uditiva non sia direttamente coinvolta nella procedura visuo-motoria di AP. Questo risultato ci ha suggerito che il codice spaziale utilizzato per rappresentare il tempo, è un meccanismo centrale che viene influenzato ad alti livelli della cognizione spaziale. La tesi prosegue con l’indagine delle aree corticali che mediano l’interazione spazio-tempo, attraverso metodi neuropsicologici, neurofisiologici e di neuroimmagine. In particolare abbiamo evidenziato che, le aree localizzate nell’emisfero destro, sono cruciali per l’elaborazione del tempo, mentre le aree localizzate nell’emisfero sinistro sono cruciali ai fini della procedura di AP e affinché AP abbia effetto sugli intervalli temporali. Infine, la tesi, è dedicata allo studio dei disturbi della rappresentazione spaziale del tempo. I risultati ci indicano che un deficit di attenzione-spaziale, dopo danno emisferico destro, provoca un deficit di rappresentazione spaziale del tempo, che si riflette negativamente sulla vita quotidiana dei pazienti. Particolarmente interessanti sono i risultati ottenuti mediante AP. Un trattamento con AP, efficace nel ridurre il deficit di attenzione-spaziale, riduce anche il deficit di rappresentazione spaziale del tempo, migliorando la qualità di vita dei pazienti.

On the renormalization flow representation of field theory and some applications

In this thesis we discuss a representation of quantum mechanics and quantum and statistical field theory based on a functional renormalization flow equation for the one-particle-irreducible average effective action, and we employ it to get information on some specific systems.

Interpreting Judgements using Knowledge Representation Methods and Computational Models of Argument

The goal of the present research is to define a Semantic Web framework for precedent modelling, by using knowledge extracted from text, metadata, and rules, while maintaining a strong text-to-knowledge morphism between legal text and legal concepts, in order to fill the gap between legal document and its semantics. The framework is composed of four different models that make use of standard languages from the Semantic Web stack of technologies: a document metadata structure, modelling the main parts of a judgement, and creating a bridge between a text and its semantic annotations of legal concepts; a legal core ontology, modelling abstract legal concepts and institutions contained in a rule of law; a legal domain ontology, modelling the main legal concepts in a specific domain concerned by case-law; an argumentation system, modelling the structure of argumentation. The input to the framework includes metadata associated with judicial concepts, and an ontology library representing the structure of case-law. The research relies on the previous efforts of the community in the field of legal knowledge representation and rule interchange for applications in the legal domain, in order to apply the theory to a set of real legal documents, stressing the OWL axioms definitions as much as possible in order to enable them to provide a semantically powerful representation of the legal document and a solid ground for an argumentation system using a defeasible subset of predicate logics. It appears that some new features of OWL2 unlock useful reasoning features for legal knowledge, especially if combined with defeasible rules and argumentation schemes. The main task is thus to formalize legal concepts and argumentation patterns contained in a judgement, with the following requirement: to check, validate and reuse the discourse of a judge - and the argumentation he produces - as expressed by the judicial text.

Sparse Signal Representation of Ultrasonic Signals for Structural Health Monitoring Applications

Assessment of the integrity of structural components is of great importance for aerospace systems, land and marine transportation, civil infrastructures and other biological and mechanical applications. Guided waves (GWs) based inspections are an attractive mean for structural health monitoring. In this thesis, the study and development of techniques for GW ultrasound signal analysis and compression in the context of non-destructive testing of structures will be presented. In guided wave inspections, it is necessary to address the problem of the dispersion compensation. A signal processing approach based on frequency warping was adopted. Such operator maps the frequencies axis through a function derived by the group velocity of the test material and it is used to remove the dependence on the travelled distance from the acquired signals. Such processing strategy was fruitfully applied for impact location and damage localization tasks in composite and aluminum panels. It has been shown that, basing on this processing tool, low power embedded system for GW structural monitoring can be implemented. Finally, a new procedure based on Compressive Sensing has been developed and applied for data reduction. Such procedure has also a beneficial effect in enhancing the accuracy of structural defects localization. This algorithm uses the convolutive model of the propagation of ultrasonic guided waves which takes advantage of a sparse signal representation in the warped frequency domain. The recovery from the compressed samples is based on an alternating minimization procedure which achieves both an accurate reconstruction of the ultrasonic signal and a precise estimation of waves time of flight. Such information is used to feed hyperbolic or elliptic localization procedures, for accurate impact or damage localization.

Scene Reconstruction And Understanding By RGB-D Sensors

This thesis investigates interactive scene reconstruction and understanding using RGB-D data only. Indeed, we believe that depth cameras will still be in the near future a cheap and low-power 3D sensing alternative suitable for mobile devices too. Therefore, our contributions build on top of state-of-the-art approaches to achieve advances in three main challenging scenarios, namely mobile mapping, large scale surface reconstruction and semantic modeling. First, we will describe an effective approach dealing with Simultaneous Localization And Mapping (SLAM) on platforms with limited resources, such as a tablet device. Unlike previous methods, dense reconstruction is achieved by reprojection of RGB-D frames, while local consistency is maintained by deploying relative bundle adjustment principles. We will show quantitative results comparing our technique to the state-of-the-art as well as detailed reconstruction of various environments ranging from rooms to small apartments. Then, we will address large scale surface modeling from depth maps exploiting parallel GPU computing. We will develop a real-time camera tracking method based on the popular KinectFusion system and an online surface alignment technique capable of counteracting drift errors and closing small loops. We will show very high quality meshes outperforming existing methods on publicly available datasets as well as on data recorded with our RGB-D camera even in complete darkness. Finally, we will move to our Semantic Bundle Adjustment framework to effectively combine object detection and SLAM in a unified system. Though the mathematical framework we will describe does not restrict to a particular sensing technology, in the experimental section we will refer, again, only to RGB-D sensing. We will discuss successful implementations of our algorithm showing the benefit of a joint object detection, camera tracking and environment mapping.