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Now showing 1 - 8 of 8
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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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    A First Step Towards Cage-based Deformation in Virtual Reality
    (The Eurographics Association, 2020) Scalas, Andreas; Zhu, Yuanju; Giannini, Franca; Lou, Ruding; Lupinetti, Katia; Monti, Marina; Mortara, Michela; Spagnuolo, Michela; Biasotti, Silvia and Pintus, Ruggero and Berretti, Stefano
    The advent of low cost technologies makes the use of immersive virtual environments more interesting for several application contexts. 3D models are largely used in such environments for providing feelings of immersion and presence in the virtual world. 3D models are normally defined in dedicated authoring tools and then adapted to be used in the virtual environments; thus, any change in the model requires to loop back to the authoring tool for performing the wished modification and the successive adaptation processes. The availability of shape modification capabilities within the virtual environment can avoid the above modification-adaptation loop. To this aim, we present our first step in the development of a 3D modelling system in Virtual Reality. The shape modification is achieved through a cage-based deformation approach, applied to semantically enriched meshes, carrying annotated meaningful regions, thus allowing the direct selection and editing of significant object parts.
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    Approximating Shapes with Standard and Custom 3D Printed LEGO Bricks
    (The Eurographics Association, 2021) Fanni, Filippo Andrea; Dal Bello, Alberto; Sbardellini, Simone; Giachetti, Andrea; Frosini, Patrizio and Giorgi, Daniela and Melzi, Simone and Rodolà, Emanuele
    In this paper, we present a work-in-progress aimed at developing a pipeline for the fabrication of shapes reproducing digital models with a combination of standard LEGO bricks and 3D printed custom elements. The pipeline starts searching for the ideal alignment of the 3D model with the brick grid. It then employs a novel approach for shape "legolization" using a outside-in heuristic to limit critical configuration, and separates an external shell and an internal part. Finally, it exploits shape booleans to create the external custom parts to be 3D printed.
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    CAD 3D Model Classification by Graph Neural Networks: A new Approach based on STEP Format
    (The Eurographics Association, 2022) Mandelli, Lorenzo; Berretti, Stefano; Cabiddu, Daniela; Schneider, Teseo; Allegra, Dario; Catalano, Chiara Eva; Cherchi, Gianmarco; Scateni, Riccardo
    In this paper, we introduce a new approach for retrieval and classification of 3D models that directly performs in the Computer- Aided Design (CAD) format without any conversion to other representations like point clouds or meshes, thus avoiding any loss of information. Among the various CAD formats, we consider the widely used STEP extension, which represents a standard for product manufacturing information. This particular format represents a 3D model as a set of primitive elements such as surfaces and vertices linked together. In our approach, we exploit the linked structure of STEP files to create a graph in which the nodes are the primitive elements and the arcs are the connections between them. We then use Graph Neural Networks (GNNs) to solve the problem of model classification. Finally, we created two datasets of 3D models in native CAD format, respectively, by collecting data from the Traceparts model library and from the Configurators software modeling company. We used these datasets to test and compare our approach with respect to state-of-the-art methods that consider other 3D formats. Our code is available at https://github.com/divanoLetto/3D_STEP_Classification
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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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    Outside-in Priority-based Approximation of 3D Models in LEGO Bricks
    (The Eurographics Association, 2022) Fanni, Filippo Andrea; Rossi, Elisa De; Giachetti, Andrea; Cabiddu, Daniela; Schneider, Teseo; Allegra, Dario; Catalano, Chiara Eva; Cherchi, Gianmarco; Scateni, Riccardo
    In this paper, we discuss the problem of converting a 3D mesh into an assembly of LEGO blocks. The major challenge of this task is how to aggregate the voxels derived by the shape discretization into a set of standard bricks guaranteeing global connectivity. We propose an outside-in priority-based heuristic method based on the analysis of the critical regions that are more likely to cause the creation of a legal assembly to fail. We show that our graph-building heuristic provides relevant advantages, making it easier to obtain a connected graph with good properties with respect to the layer-based or random aggregation strategies applied in most of the optimization approaches. We also propose BRICKS, a novel dataset for the evaluation of aggregation strategies. It includes voxelizations at 3 different resolutions of 33 shapes and allows the easy comparison of different voxel aggregation strategies independently of the shape discretization step and also considering their scalability. We use it to evaluate our approach with respect to graph-based connectivity measures, showing the advantages of the proposed strategy.
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    Recognition, Modelling and Interactive Manipulation of Motifs or Symbols Represented by a Composition of Curves
    (The Eurographics Association, 2020) Romanengo, Chiara; Brunetto, Erika; Biasotti, Silvia; Catalano, Chiara Eva; Falcidieno, Bianca; Biasotti, Silvia and Pintus, Ruggero and Berretti, Stefano
    In this work we introduce a method for the recognition, modelling and interactive manipulation of graphical motifs, symbols or artistic elements that are represented by a composition of plane curves. Our method bases on Hough transform (HT) concepts, in particular on its generalisation to algebraic curves. We recognise complex curves and their compositions starting from images or point clouds, we represent them in implicit or parametric form, and their parameters are calculated together with their relationships. Besides the recognition of curves and modelling by algebraic equations, we propose a visualisation and manipulation tool developed on a multi-touch table. The objective of this application is to support an interactive manipulation of any geometric motifs or symbols with or without imposing the constraints derived from the identified relations among the curve parameters. Finally, we validate the proposed method showing its application to three detailed case studies, which differ in type and creation mode.
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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.