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Now showing 1 - 7 of 7
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    HT-based Recognition of Patterns on 3D Shapes Using a Dictionary of Mathematical Curves
    (The Eurographics Association, 2019) Romanengo, Chiara; Biasotti, Silvia; FALCIDIENO, BIANCA; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    Characteristic curves play a fundamental role in the way a shape is perceived and illustrated. To address the curve recognition problem on surfaces, we adopt a generalisation of the Hough Transform (HT) which is able to deal with mathematical curves. In particular, we extend the set of curves so far adopted for curve recognition with the HT and propose a new dictionary of curves to be selected as templates. In addition, we introduce rules of composition and aggregation of curves into patterns, not limiting the recognition to a single curve at a time. Our method recognises various curves and patterns, possibly compound on a 3D surface. It selects the most suitable profile in a family of curves and, deriving from the HT, it is robust to noise and able to deal with data incompleteness. The system we have implemented is open and allows new additions of curves in the dictionary of functions already available.
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    CageLab: an Interactive Tool for Cage-Based Deformations
    (The Eurographics Association, 2018) Casti, S.; Corda, F.; Livesu, M.; Scateni, R.; Livesu, Marco and Pintore, Gianni and Signoroni, Alberto
    Posing a digital character by acting on the vertices of a coarse control cage is, after skeleton-based, probably the most widely used technique for digital animation. While skeleton-based techniques have been deeply researched and a variety of industrial and academic tools are available for it, cage-based techniques have historically received less attention. In recent years we observed an increasing interest in the field, which results in a growing number of publications both on algorithms for automatic or semi-automatic cage generation, and for smooth barycentric coordinates for general polyhedral meshes. We introduce CageLab: a novel research-oriented software tool that allows scholars and practitioners in general to get acquainted with cagebased animation in a lightweight and easy to use environment. Users can: (i) load digital characters and their associated cages, applying character deformations with a selection of the most widely used barycentric coordinates available in literature; (ii) compare alternative cages for a given digital character; (iii) compare alternative barycentric coordinates w.r.t their smoothness and locality within the cage; (iv) use CageLab for educational purposes, or to produce images and videos for scientific articles. We publicly release the tool to the community, with the hope to support this growth, and possibly foster even more research in the field.
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    A Study on Natural 3D Shape Manipulation in VR
    (The Eurographics Association, 2018) Cordeiro, E.; Giannini, F.; Monti, M.; Mendes, D.; Ferreira, A.; Livesu, Marco and Pintore, Gianni and Signoroni, Alberto
    Current immersive modeling environments use non-natural tools and interfaces to support traditional shape manipulation operations. In the future, we expect the availability of natural methods of interaction with 3D models in immersive environments to become increasingly important in several industrial applications. In this paper, we present a study conducted on a group of potential users with the aim of verifying if there is a common strategy in gestural and vocal interaction in immersive environments when the objective is modifying a 3D shape model. The results indicate that users adopt different strategies to perform the different tasks but in the execution of a specific activity it is possible to identify a set of similar and recurrent gestures. In general, the gestures made are physically plausible. During the experiment, the vocal interaction was used quite rarely and never to express a command to the system but rather to better specify what the user was doing with gestures.
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    Simplification of Shapes for Fabrication with V-Groove Milling Tools
    (The Eurographics Association, 2018) Muntoni, A.; Scalas, A.; Nuvoli, S.; Scateni, R.; Livesu, Marco and Pintore, Gianni and Signoroni, Alberto
    We introduce here a pipeline for simplifying digital 3D shapes with the aim of fabricating them using 2D polygonal flat parts. Our method generates shapes that, once unfolded, can be fabricated with CNC milling machines using special tools called V-Grooves. These tools make V-shaped furrows at given angles depending on the shape of the used tool. Milling the edges of each flat facet simplifies the manual assembly that consists only in folding the facets at the desired angle between the adjacent facets. Our method generates simplified shapes where every dihedral angle between adjacent facets belongs to a restricted set, thus making the assembly process quicker and more straightforward. Firstly, our method automatically computes a simplification of the model, iterating local changes on a triangle mesh generated by applying the Marching Cubes algorithm on the original mesh. The user performs a second manual simplification using a tool that removes spurious facets. Finally, we use a simple unfolding algorithm which flattens the polygonal facets onto the 2D plane, so that a CNC milling machine can fabricate it with a sheet of rigid material.
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    Indicators Basis for Functional Shape Analysis
    (The Eurographics Association, 2018) Melzi, S.; Livesu, Marco and Pintore, Gianni and Signoroni, Alberto
    Step functions are widely used in several applications from geometry processing and shape analysis. Shape segmentation, partial matching and self similarity detection just to name a few. The standard signal processing tools do not allow us to fully handle this class of functions. The classical Fourier series, for instance, does not give a good representation for these non smooth functions. In this paper we define a new basis for the approximation and transfer of the step functions between shapes. Our definition is fully spectral, allowing for a concise representation and an efficient computation. Furthermore our basis is specifically built in order to enhance its use in combination with the functional maps framework. The functional approach also enable us to handle shape deformations. Thanks to that our basis achieves a large improvement not only in the approximation of step functions but also in the transfer, exploiting the functional maps framework. We perform a large set of experiments showing the improvement achieved by the proposed basis in the approximation and transfer of step functions and its stability with respect to non isometric deformations.
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    Computational Fabrication of Macromolecules to Enhance Perception and Understanding of Biological Mechanisms
    (The Eurographics Association, 2019) Alderighi, Thomas; Giorgi, Daniela; Malomo, Luigi; Cignoni, Paolo; Zoppè, Monica; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    We propose a fabrication technique for the fast and cheap production of 3D replicas of proteins. We leverage silicone casting with rigid molds, to produce flexible models which can be safely extracted from the mold, and easily manipulated to simulate the biological interaction mechanisms between proteins. We believe that tangible models can be useful in education as well as in laboratory settings, and that they will ease the understanding of fundamental principles of macromolecular organization.
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    Feature-based Characterisation of Patient-specific 3D Anatomical Models
    (The Eurographics Association, 2019) Banerjee, Imon; Paccini, Martina; Ferrari, Enrico; CATALANO, CHIARA EVA; Biasotti, Silvia; Spagnuolo, Michela; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    This paper aims to examine the potential of 3D shape analysis integrated to machine learning techniques in supporting medical investigation. In particular, we introduce an approach specially designed for the characterisation of anatomical landmarks on patient-specific 3D carpal bone models represented as triangular meshes. Furthermore, to identify functional articulation regions, two novel district-based properties are defined. The performance of both state of the art and novel features has been evaluated in a machine learning setting to identify a set of significant anatomical landmarks on patient data. Experiments have been performed on a carpal dataset of 56 patient-specific 3D models that are segmented from T1 weighed magnetic resonance (MR) scans of healthy male subjects. Despite the typical large inter-patient shape variation within the training samples, our framework has achieved promising results.