1,721,170 research outputs found
Low Resolution Image Sampling for Pattern Matching
No full textThe paper presents a simulated mobile system that learns to solve the egolocation task in a known environment, in a supervised way, using a very low resolution sampling of the optical array and RBF approximation techniques. The impact of the number of sensors, of their layout, in particular of Sobol sequences with respect to regular grids for a progressively refined sampling of images, and of the complexity of response of each sensing unit has been investigated in an attempt to simplify as much as possible the architecture of the image processing module retaining good localization ability
Identity Verification through Finger Matching: A Comparison of Support Vector Machines and Gaussian Basis Function Classifiers
No full textThe paper presents a people identity verification system based on the matching of top view finger snapshots, supplementing purely geometrical finger shape comparison with textural information. Low dimensional feature vectors are used to train binary classifiers based on small Gaussian Basis Functions networks which, in this task, are able to match Support Vector Machines performance while outperforming them in runtime effciency, thereby exposing a different facet in the comparison which complements available literature reports
Template matching techniques in computer vision: theory and practice
No full textThe detection and recognition of objects in images is a key research topic in the computer vision community. Within this area, face recognition and interpretation has attracted increasing attention owing to the possibility of unveiling human perception mechanisms, and for the development of practical biometric systems. This book and the accompanying website, focus on template matching, a subset of object recognition techniques of wide applicability, which has proved to be particularly effective for face recognition applications. Using examples from face processing tasks throughout the book to illustrate more general object recognition approaches, Roberto Brunelli: examines the basics of digital image formation, highlighting points critical to the task of template matching;presents basic and advanced template matching techniques, targeting grey-level images, shapes and point sets;discusses recent pattern classification paradigms from a template matching perspective;illustrates the development of a real face recognition system;explores the use of advanced computer graphics techniques in the development of computer vision algorithms. Template Matching Techniques in Computer Vision is primarily aimed at practitioners working on the development of systems for effective object recognition such as biometrics, robot navigation, multimedia retrieval and landmark detection. It is also of interest to graduate students undertaking studies in these areas
Rilevanza dell’ubriachezza del lavoratore nella causazione dell’infortunio
No full text[Relevancy of the drunkenness of the employee in causing accident] The
Supreme Court considers irrelevant the reckless behavior of the worker who is
injured, constantly arguing that every accident can be widely expected by the
employer who must then locate precautionary measures designed to prevent
it. This article sets out to denounce the unsustainability of a dogmatic
approach, that involves a constant overlap of causality and guilt, to highlight
that workers must be able to manage their own area of risk, and to point out
that drunkenness cannot be assimilated to carelessness, since it is predictable
only by the worker
Template Matching Techniques in Computer Vision
No full textTemplate matching: una rivisitazione dei fondamenti - Il rilevamento di strutture all'interno di immagini viene descritto evidenziando i problemi connessi all'acquisizione di immagini, all'effetto del rumore, alla variabilita' delle strutture e delle loro condizioni di ripresa. Il rilevamento di una struttura data all'interno di immagini (template matching) e' presentato poi come un problema statistico di test di ipotesi. Dopo l'introduzione dei paradigmi di Bayes e Neyman-Pearson viene affrontato il problema della classificazione nel caso di rumore gaussiano. Vengono poi definiti alcuni concetti di base riguardanti gli stimatori e presentato il metodo di shrinking (James-Stein), utile nella stima di matrici di covarianza quando sono disponibili pochi dati. Viene poi analizzato il problema della caratterizzazione delle prestazioni di un sistema di template matching, dalla valutazione degli errori, alla stima della accuratezza, alla generazione di esempi sintetici
Estimation of Pose and Illuminant Direction for Face Processing
No full textIn this paper three problems related to the analysis of facial images are addressed: the estimation of the illuminant direction, the compensation of illumination effects and, finally, the recovery of the pose of the face, restricted to in-depth rotations. The solutions proposed for these problems rely on the use of computer graphics techniques to provide images of faces under different illumination and pose, starting from a database of frontal views under frontal illuminatio
Aspetti penali della sicurezza sul lavoro
No full textIl lavoro si propone di verificare i fondamentali obblighi gravanti sulle figure di riferimento classiche (datore di lavoro, dirigente e preposto) e nuove (R.S.P.P.; medico competente; R.L.S.) delineate dal D.Lvo 626/94 con particolare attenzione al tema del c.d. “adeguamento tecnologico”
Monitoring Crowding Level: Visual Learning in Virtual Environments
No full textThe paper presents a solution to the problem of crowding estimation in large environments using multiple visual sensors. The proposed approach presents innovations addressing several information processing stages of a surveillance system. A novel, robust way to manage shadows in low resolution, color or monochrome images, is introduced providing reliable background subtraction. The resulting robust foreground pixel count is mapped into people count by a new learning algorithm that samples the environment in an adaptive way by directing a human probe to stabilize its results. The maps from multiple sensors are then automatically aligned into a global, two dimensional, reference coordinate system without requiring explicit sensor calibration. This feature supports information integration and the development of fault tolerant surveillance systems. Algorithm development and performance assessment rely on an innovative methodology based on photo-realistic synthetic museum environments populated by virtual visitors. The simulator provides a flexible test bed for the investigation of automatic surveillance systems. As a sample application, the resulting occupancy maps are then used to characterize people flow patterns at different crowding levels exposing possible visiting bottlenecks
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