Italian Chapter Conference 2019 - Smart Tools and Apps in computer Graphics

Permanent URI for this collection

Cagliari, Italy, November 14 – 15, 2019
Full Papers
MTV-Player: Interactive Spatio-Temporal Exploration of Compressed Large-Scale Time-Varying Rectilinar Scalar Volumes
Jose Díaz, Fabio Marton, and Enrico Gobbetti
A Visualization Tool for Scholarly Data
Mario Salinas, Daniela Giorgi, Federico Ponchio, and Paolo Cignoni
Immersive Environment for Creating, Proofreading, and Exploring Skeletons of Nanometric Scale Neural Structures
Daniya Boges, Corrado Calì, Pierre J. Magistretti, Markus Hadwiger, Ronell Sicat, and Marco Agus
HT-based Recognition of Patterns on 3D Shapes Using a Dictionary of Mathematical Curves
Chiara Romanengo, Silvia Biasotti, and Bianca Falcidieno
Feature-based Characterisation of Patient-specific 3D Anatomical Models
Imon Banerjee, Martina Paccini, Enrico Ferrari, Chiara Eva Catalano, Silvia Biasotti, and Michela Spagnuolo
3DReg-i-Net: Improving Deep Learning Based 3D Registration for a Robust Real-time Alignment of Small-scale Scans
Marco Lombardi, Andrea Riccardi, Mattia Savardi, and Alberto Signoroni
Split and Mill: User Assisted Height-field Block Decomposition for Fabrication
Alessandro Muntoni, Lucio Davide Spano, and Riccardo Scateni
Interactive Animation of Single-layer Cumulus Clouds Using Cloud Map
Prashant Goswami
Motion Data and Model Management for Applied Statistical Motion Synthesis
Erik Herrmann, Han Du, André Antakli, Dmitri Rubinstein, René Schubotz, Janis Sprenger, Somayeh Hosseini, Noshaba Cheema, Ingo Zinnikus, Martin Manns, Klaus Fischer, and Philipp Slusallek
Visual Representation of Region Transitions in Multi-dimensional Parameter Spaces
Oliver Fernandes, Steffen Frey, Guido Reina, and Thomas Ertl
Posters
Design and Implementation of a Visualization Tool for the in-depth Analysis of the Domestic Electricity Consumption
Gabriele Merlin, Daniele Ortu, Gianmarco Cherchi, and Riccardo Scateni
Computational Fabrication of Macromolecules to Enhance Perception and Understanding of Biological Mechanisms
Thomas Alderighi, Daniela Giorgi, Luigi Malomo, Paolo Cignoni, and Monica Zoppè
MLIC-Synthetizer: a Synthetic Multi-Light Image Collection Generator
Tinsae Gebrechristos Dulecha, Andrea Dall'Alba, and Andrea Giachetti
Mapping Grey-Levels on 3D Segmented Anatomical districts
Martina Paccini, Giuseppe Patané, and Michela Spagnuolo
Relief Pattern Segmentation Using 2D-Grid Patches on a Locally Ordered Mesh Manifold
Claudio Tortorici, Denis Vreshtazi, Stefano Berretti, and Naoufel Werghi
Full Papers
Yocto/GL: A Data-Oriented Library For Physically-Based Graphics
Fabio Pellacini, Giacomo Nazzaro, and Edoardo Carra
The Py3DViewer Project: a Python Library for fast Prototyping in Geometry Processing
Gianmarco Cherchi, Luca Pitzalis, Giovanni Laerte Frongia, and Riccardo Scateni
ReVize: A Library for Visualization Toolchaining with Vega-Lite
Marius Hogräfer and Hans-Jörg Schulz

BibTeX (Italian Chapter Conference 2019 - Smart Tools and Apps in computer Graphics)
@inproceedings{
10.2312:stag.20191359,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
A Visualization Tool for Scholarly Data}},
author = {
Salinas, Mario
and
Giorgi, Daniela
and
Ponchio, Federico
and
Cignoni, Paolo
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191359}
}
@inproceedings{
10.2312:stag.20191358,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
MTV-Player: Interactive Spatio-Temporal Exploration of Compressed Large-Scale Time-Varying Rectilinar Scalar Volumes}},
author = {
Díaz, Jose
and
Marton, Fabio
and
Gobbetti, Enrico
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191358}
}
@inproceedings{
10.2312:stag.20191361,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
HT-based Recognition of Patterns on 3D Shapes Using a Dictionary of Mathematical Curves}},
author = {
Romanengo, Chiara
and
Biasotti, Silvia
and
FALCIDIENO, BIANCA
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191361}
}
@inproceedings{
10.2312:stag.20191360,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
Immersive Environment for Creating, Proofreading, and Exploring Skeletons of Nanometric Scale Neural Structures}},
author = {
Boges, Daniya
and
Calì, Corrado
and
Magistretti, Pierre J.
and
Hadwiger, Markus
and
Sicat, Ronell
and
Agus, Marco
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191360}
}
@inproceedings{
10.2312:stag.20191362,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
Feature-based Characterisation of Patient-specific 3D Anatomical Models}},
author = {
Banerjee, Imon
and
Paccini, Martina
and
Ferrari, Enrico
and
CATALANO, CHIARA EVA
and
Biasotti, Silvia
and
Spagnuolo, Michela
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191362}
}
@inproceedings{
10.2312:stag.20191364,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
Split and Mill: User Assisted Height-field Block Decomposition for Fabrication}},
author = {
Muntoni, Alessandro
and
SPANO, LUCIO DAVIDE
and
Scateni, Riccardo
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191364}
}
@inproceedings{
10.2312:stag.20191363,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
3DReg-i-Net: Improving Deep Learning Based 3D Registration for a Robust Real-time Alignment of Small-scale Scans}},
author = {
Lombardi, Marco
and
Riccardi, Andrea
and
Savardi, Mattia
and
Signoroni, Alberto
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191363}
}
@inproceedings{
10.2312:stag.20191365,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
Interactive Animation of Single-layer Cumulus Clouds Using Cloud Map}},
author = {
Goswami, Prashant
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191365}
}
@inproceedings{
10.2312:stag.20191367,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
Visual Representation of Region Transitions in Multi-dimensional Parameter Spaces}},
author = {
Fernandes, Oliver
and
Frey, Steffen
and
Reina, Guido
and
Ertl, Thomas
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191367}
}
@inproceedings{
10.2312:stag.20191366,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
Motion Data and Model Management for Applied Statistical Motion Synthesis}},
author = {
Herrmann, Erik
and
Du, Han
and
Fischer, Klaus
and
Slusallek, Philipp
and
Antakli, André
and
Rubinstein, Dmitri
and
Schubotz, René
and
Sprenger, Janis
and
Hosseini, Somayeh
and
Cheema, Noshaba
and
Zinnikus, Ingo
and
Manns, Martin
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191366}
}
@inproceedings{
10.2312:stag.20191368,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
Design and Implementation of a Visualization Tool for the in-depth Analysis of the Domestic Electricity Consumption}},
author = {
Merlin, Gabriele
and
Ortu, Daniele
and
Cherchi, Gianmarco
and
Scateni, Riccardo
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191368}
}
@inproceedings{
10.2312:stag.20191371,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
Mapping Grey-Levels on 3D Segmented Anatomical districts}},
author = {
Paccini, Martina
and
Patané, Giuseppe
and
Spagnuolo, Michela
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191371}
}
@inproceedings{
10.2312:stag.20191369,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
Computational Fabrication of Macromolecules to Enhance Perception and Understanding of Biological Mechanisms}},
author = {
Alderighi, Thomas
and
Giorgi, Daniela
and
Malomo, Luigi
and
Cignoni, Paolo
and
Zoppè, Monica
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191369}
}
@inproceedings{
10.2312:stag.20191370,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
MLIC-Synthetizer: a Synthetic Multi-Light Image Collection Generator}},
author = {
Dulecha, Tinsae Gebrechristos
and
Dall'Alba, Andrea
and
Giachetti, Andrea
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191370}
}
@inproceedings{
10.2312:stag.20191372,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
Relief Pattern Segmentation Using 2D-Grid Patches on a Locally Ordered Mesh Manifold}},
author = {
Tortorici, Claudio
and
Vreshtazi, Denis
and
Berretti, Stefano
and
Werghi, Naoufel
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191372}
}
@inproceedings{
10.2312:stag.20191373,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
Yocto/GL: A Data-Oriented Library For Physically-Based Graphics}},
author = {
Pellacini, Fabio
and
Nazzaro, Giacomo
and
Carra, Edoardo
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191373}
}
@inproceedings{
10.2312:stag.20191374,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
The Py3DViewer Project: A Python Library for fast Prototyping in Geometry Processing}},
author = {
Cherchi, Gianmarco
and
Pitzalis, Luca
and
Frongia, Giovanni Laerte
and
Scateni, Riccardo
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191374}
}
@inproceedings{
10.2312:stag.20191375,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
editor = {
Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
}, title = {{
ReVize: A Library for Visualization Toolchaining with Vega-Lite}},
author = {
Hogräfer, Marius
and
Schulz, Hans-Jörg
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-100-7},
DOI = {
10.2312/stag.20191375}
}

Browse

Recent Submissions

Now showing 1 - 19 of 19
  • Item
    STAG 2019: Frontmatter
    (Eurographics Association, 2019) Agus, Marco; Corsini, Massimiliano; Pintus, Ruggero; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
  • Item
    A Visualization Tool for Scholarly Data
    (The Eurographics Association, 2019) Salinas, Mario; Giorgi, Daniela; Ponchio, Federico; Cignoni, Paolo; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    We propose ReviewerNet, an online, interactive visualization system aimed to improve the reviewer selection process in the academic domain. Given a paper submitted for publication, we assume that good candidate reviewers can be chosen among the authors of a small set of pertinent papers; ReviewerNet supports the construction of such set of papers, by visualizing and exploring a literature citation network. Then, the system helps to select reviewers that are both well distributed in the scientific community and that do not have any conflict-of-interest, by visualising the careers and co-authorship relations of candidate reviewers. The system is publicly available, and is demonstrated in the field of Computer Graphics.
  • Item
    MTV-Player: Interactive Spatio-Temporal Exploration of Compressed Large-Scale Time-Varying Rectilinar Scalar Volumes
    (The Eurographics Association, 2019) Díaz, Jose; Marton, Fabio; Gobbetti, Enrico; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    We present an approach for supporting fully interactive exploration of massive time-varying rectilinear scalar volumes on commodity platforms. We decompose each frame into a forest of bricked octrees. Each brick is further subdivided into smaller blocks, which are compactly approximated by quantized variable-length sparse linear combinations of prototype blocks stored in a data-dependent dictionary learned from the input sequence. This variable bit-rate compact representation, obtained through a tolerance-driven learning and approximation process, is stored in a GPU-friendly format that supports direct adaptive streaming to the GPU with spatial and temporal random access. An adaptive compression-domain renderer closely coordinates off-line data selection, streaming, decompression, and rendering. The resulting system provides total control over the spatial and temporal dimensions of the data, supporting the same exploration metaphor as traditional video players. Since we employ a highly compressed representation, the bandwidth provided by current commodity platforms proves sufficient to fully stream and render dynamic representations without relying on partial updates, thus avoiding any unwanted dynamic effects introduced by current incremental loading approaches. Moreover, our variable-rate encoding based on sparse representations provides high-quality approximations, while offering real-time decoding and rendering performance. The quality and performance of our approach is demonstrated on massive time-varying datasets at the terascale, which are nonlinearly explored at interactive rates on a commodity graphics PC.
  • Item
    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.
  • Item
    Immersive Environment for Creating, Proofreading, and Exploring Skeletons of Nanometric Scale Neural Structures
    (The Eurographics Association, 2019) Boges, Daniya; Calì, Corrado; Magistretti, Pierre J.; Hadwiger, Markus; Sicat, Ronell; Agus, Marco; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    We present a novel immersive environment for the exploratory analysis of nanoscale cellular reconstructions of rodent brain samples acquired through electron microscopy. The system is focused on medial axis representations (skeletons) of branched and tubular structures of brain cells, and it is specifically designed for: i) effective semi-automatic creation of skeletons from surface-based representations of cells and structures, ii) fast proofreading, i.e., correcting and editing of semi-automatically constructed skeleton representations, and iii) useful exploration, i.e., measuring, comparing, and analyzing geometric features related to cellular structures based on medial axis representations. The application runs in a standard PC-tethered virtual reality (VR) setup with a head mounted display (HMD), controllers, and tracking sensors. The system is currently used by neuroscientists for performing morphology studies on sparse reconstructions of glial cells and neurons extracted from a sample of the somatosensory cortex of a juvenile rat.
  • Item
    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.
  • Item
    Split and Mill: User Assisted Height-field Block Decomposition for Fabrication
    (The Eurographics Association, 2019) Muntoni, Alessandro; SPANO, LUCIO DAVIDE; Scateni, Riccardo; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    We present here Split and Mill: an interactive system for the manual volume decomposition of free form shapes. Our primary purpose is to generate portions respecting the properties allowing to mill them with a 3-axis milling machine. We show that a manual decomposition is competitive with the automatic partitioning when the user is skilled enough. We, thus, think that our tool can be beneficial for the practitioners in the field, and we release it as free software.
  • Item
    3DReg-i-Net: Improving Deep Learning Based 3D Registration for a Robust Real-time Alignment of Small-scale Scans
    (The Eurographics Association, 2019) Lombardi, Marco; Riccardi, Andrea; Savardi, Mattia; Signoroni, Alberto; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    We present 3DReg-i-Net, an improved deep learning solution for pairwise registration of 3D scans, which evolves the recently proposed 3DRegNet technique by Pais et al. This is one of the very first learning based algorithm aiming at producing the co-registration of two 3D views starting solely from a set of point correspondences, which is able to perform outlier rejection and to recover the registration matrix. We evolve the original method to face the challenging scenario of quick 3D modelling at small scales through the alignment of dense 3D views acquired at video frame-rate with a handheld scanner. We improve the system tracking robustness and alignment performance with a generalized input data augmentation. Moreover, working on suboptimal aspects of the original solution, we propose different improvements that lead to a redefinition of the training loss function. When tested on the considered scenario, the proposed 3DReg-i-Net significantly outperforms the prior solution in terms of accuracy of the estimated aligning transforms.
  • Item
    Interactive Animation of Single-layer Cumulus Clouds Using Cloud Map
    (The Eurographics Association, 2019) Goswami, Prashant ; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    In this paper, we present a physics-driven procedural method for the interactive animation of realistic, single-layered cumulus clouds for the landscape-scale size. Our method employs the coarse units called parcels for the physics simulation and achieves procedural micro-level volumetric amplification based on the macro physics parameters. However, contrary to the previous methods which achieve amplification directly inside the parcels, we make use of the two-dimensional texture called cloud maps to this end. This not only improves the shape and distribution of the cloud cover over the landscape but also boosts the animation efficiency significantly, allowing the overall approach to run at high frame rates, which is verified by the experiments presented in the paper.
  • Item
    Visual Representation of Region Transitions in Multi-dimensional Parameter Spaces
    (The Eurographics Association, 2019) Fernandes, Oliver; Frey, Steffen; Reina, Guido; Ertl, Thomas; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    We propose a novel visual representation of transitions between homogeneous regions in multi-dimensional parameter space. While our approach is generally applicable for the analysis of arbitrary continuous parameter spaces, we particularly focus on scientific applications, like physical variables in simulation ensembles. To generate our representation, we use unsupervised learning to cluster the ensemble members according to their mutual similarity. In doing this, clusters are sorted such that similar clusters are located next to each other. We then further partition the clusters into connected regions with respect to their location in parameter space. In the visualization, the resulting regions are represented as glyphs in a matrix, indicating parameter changes which induce a transition to another region. To unambiguously associate a change of data characteristics to a single parameter, we specifically isolate changes by dimension. With this, our representation provides an intuitive visualization of the parameter transitions that influence the outcome of the underlying simulation or measurement. We demonstrate the generality and utility of our approach on diverse types of data, namely simulations from the field of computational fluid dynamics and thermodynamics, as well as an ensemble of raycasting performance data.
  • Item
    Motion Data and Model Management for Applied Statistical Motion Synthesis
    (The Eurographics Association, 2019) Herrmann, Erik; Du, Han; Antakli, André; Rubinstein, Dmitri; Schubotz, René; Sprenger, Janis; Hosseini, Somayeh; Cheema, Noshaba; Zinnikus, Ingo; Manns, Martin; Fischer, Klaus; Slusallek, Philipp; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    Machine learning based motion modelling methods such as statistical modelling require a large amount of input data. In practice, the management of the data can become a problem in itself for artists who want to control the quality of the motion models. As a solution to this problem, we present a motion data and model management system and integrate it with a statistical motion modelling pipeline. The system is based on a data storage server with a REST interface that enables the efficient storage of different versions of motion data and models. The database system is combined with a motion preprocessing tool that provides functions for batch editing, retargeting and annotation of the data. For the application of the motion models in a game engine, the framework provides a stateful motion synthesis server that can load the models directly from the data storage server. Additionally, the framework makes use of a Kubernetes compute cluster to execute time consuming processes such as the preprocessing and modelling of the data. The system is evaluated in a use case for the simulation of manual assembly workers.
  • Item
    Design and Implementation of a Visualization Tool for the in-depth Analysis of the Domestic Electricity Consumption
    (The Eurographics Association, 2019) Merlin, Gabriele; Ortu, Daniele; Cherchi, Gianmarco; Scateni, Riccardo; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    In this poster, we present a visualization tool for the in-depth analysis of domestic electricity consumption. The web-interface allows users to visualize their electricity consumption, compare them with their own records or with the means of selected communities.
  • Item
    Mapping Grey-Levels on 3D Segmented Anatomical districts
    (The Eurographics Association, 2019) Paccini, Martina; Patané, Giuseppe; Spagnuolo, Michela; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    The study aims to perform a simple but effective integration of geometric information of segmented 3D bones' surface and density information provided by volume MRI (Magnetic Resonance Imaging). Such a representation method could support diagnosis process, biomedical simulation, computed assisted surgery and prosthesis fitting. The input consists of a volume MRI of a carpal district and the corresponding 3D surface model. The algorithm superimposes image and surface, and, once found the image voxel correspondent to each surface point, maps the grey level of the voxels identified on the segmented surface. The output is a surface mesh on which the texture, induced by the MRI, has been mapped. The approach is effective, general and applicable to different anatomical districts. Further elaboration of the results can be used to perform landmark identification or segmentation correction.
  • Item
    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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    MLIC-Synthetizer: a Synthetic Multi-Light Image Collection Generator
    (The Eurographics Association, 2019) Dulecha, Tinsae Gebrechristos; Dall'Alba, Andrea; Giachetti, Andrea; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    We present MLIC-Synthetizer, a Blender plugin specifically designed for the generation of a syntethic Multi-Light Image Collection using physically-based rendering. This tool makes easy to generate large amount of test data that can be useful for Photometric Stereo algorithms evaluation, validation of Reflectance Transformation Imaging calibration and processing method, relighting methods and more. Multi-pass rendering allows the generation of images with associated shadows and specularity ground truth maps, ground truth normals and material segmentation masks. Furthermore loops on material parameters allows the automatic generation of datasets with pre-defined material parameters ranges that can be used to train robust learning-based algorithms for 3D reconstruction, relight and material segmentation.
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    Relief Pattern Segmentation Using 2D-Grid Patches on a Locally Ordered Mesh Manifold
    (The Eurographics Association, 2019) Tortorici, Claudio; Vreshtazi, Denis; Berretti, Stefano; Werghi, Naoufel; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    The mesh manifold support has been analyzed to perform several different tasks. Recently, it emerged the need for new methods capable of analyzing relief patterns on the surface. In particular, a new and not investigated problem is that of segmenting the surface according to the presence of different relief patterns. In this paper, we introduce this problem and propose a new approach for segmenting such relief patterns (also called geometric texture) on the mesh-manifold. Operating on regular and ordered mesh, we design, in the first part of the paper, a new mesh re-sampling technique complying with this requirement. This technique ensures the best trade-off between mesh regularization and geometric texture preservation, when compared with competitive methods. In the second part, we present a novel scheme for segmenting a mesh surface into three classes: texturedsurface, non-textured surface, and edges (i.e., surfaces at the border between the two). This technique leverages the ordered structure of the mesh for deriving 2D-grid patches allowing us to approach the segmentation problem as a patch-classification technique using a CNN network in a transfer learning setting. Experiments performed on surface samples from the SHREC'18 contest show remarkable performance with an overall segmentation accuracy of over 99%.
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    Yocto/GL: A Data-Oriented Library For Physically-Based Graphics
    (The Eurographics Association, 2019) Pellacini, Fabio; Nazzaro, Giacomo; Carra, Edoardo; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    In this paper we present Yocto/GL, a software library for computer graphics research and education. The library is written in C++ and targets execution on the CPU, with support for basic math, geometry and imaging utilities, path tracing and file IO. What distinguishes Yocto/GL from other similar projects is its minimalistic design and data-oriented programming style, which makes the library readable, extendible, and efficient. We developed Yocto/GL to meet our need, as a research group, of a simple and reliable codebase that lets us experiment with ease on research projects of various kind. After many iterations carried out over a few years, we settled on a design that we find effective for our purposes. In the hope of making our efforts valuable for the community, we share our experience in the development and make the library publicly available.
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    The Py3DViewer Project: A Python Library for fast Prototyping in Geometry Processing
    (The Eurographics Association, 2019) Cherchi, Gianmarco; Pitzalis, Luca; Frongia, Giovanni Laerte; Scateni, Riccardo; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    Fast research and prototyping, nowadays, is shifting towards languages that allow interactive execution and quick changes. Python is very widely used for rapid prototyping. We introduce Py3DViewer, a new Python library that allows researchers to quickly prototype geometry processing algorithms by interactively editing and viewing meshes. Polygonal and polyhedral meshes are both supported. The library is designed to be used in conjunction with Jupyter environments, which allow interactive Python code execution and data visualization in a browser, thus opening up the possibility of viewing a mesh while editing the underlying geometry and topology.
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    ReVize: A Library for Visualization Toolchaining with Vega-Lite
    (The Eurographics Association, 2019) Hogräfer, Marius; Schulz, Hans-Jörg; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    The field of tools for data visualization has been growing in recent years, with each tool contributing new ways to create and work with visualizations, and each offering a specialized set of features, interaction metaphors and user interfaces. This means on one hand that users have a wide choice in visualization tools. On the other hand, though, this choice might also lock-in the user: Once made, it becomes difficult and sometimes even impossible to switch to another tool - e.g., to further refine a visualization made in one tool inside another. In turn, users are forced to work around any shortcomings of the chosen tool, as switching to another tool is even more cumbersome. In this paper, we introduce ReVize, an open-source library for visualization toolchaining. ReVize makes use of Vega-Lite as a common exchange format to be able to add toolchain support to web-based tools. In contrast to existing approaches, this solution to visualization toolchaining allows for authoring a visualization with multiple tools in a back-and-forth fashion, without a preset order in which tools are to be used. We demonstrate ReVize by adding toolchain support to three existing tools - KNIME, ColorBrewer, and VisFlow - for using them in concert to author visualizations.