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2021 Journal article Open Access OPEN

Smart Working at CNR-ISTI in the COVID-19 Era
Scopigno R., Giorgi D.
The CNR Institute for Information Science and Technologies describes its experience in adapting to smart working, which has dramatically changed the institute's modus operandi for most of the year 2020.Source: ERCIM news (2021): 6–7.

See at: ercim-news.ercim.eu Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2020 Journal article Restricted

ReviewerNet: A visualization platform for the selection of academic reviewers
Salinas M., Giorgi D., Ponchio F., Cignoni P.
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. The system helps journal editors and Program Committee members to select reviewers that do not have any conflict-of-interest and are representative of different research groups, 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.Source: Computers & graphics 89 (2020): 77–87. doi:10.1016/j.cag.2020.04.006
DOI: 10.1016/j.cag.2020.04.006

See at: Computers & Graphics Restricted | Computers & Graphics Restricted | Computers & Graphics Restricted | Computers & Graphics Restricted | Computers & Graphics Restricted | CNR ExploRA Restricted | www.sciencedirect.com Restricted | Computers & Graphics Restricted


2020 Journal article Open Access OPEN

Optimizing object decomposition to reduce visual artifacts in 3D printing
Filoscia I., Alderighi T., Giorgi D., Malomo L., Callieri M., Cignoni P.
We propose a method for the automatic segmentation of 3D objects into parts which can be individually 3D printed and then reassembled by preserving the visual quality of the final object. Our technique focuses on minimizing the surface affected by supports, decomposing the object into multiple parts whose printing orientation is automatically chosen. The segmentation reduces the visual impact on the fabricated model producing non-planar cuts that adapt to the object shape. This is performed by solving an optimization problem that balances the effects of supports and cuts, while trying to place both in occluded regions of the object surface. To assess the practical impact of the solution, we show a number of segmented, 3D printed and reassembled objects.Source: Computer graphics forum (Print) 39 (2020): 423–434. doi:10.1111/cgf.13941
DOI: 10.1111/cgf.13941
Project(s): EVOCATION via OpenAIRE

See at: onlinelibrary.wiley.com Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | Computer Graphics Forum Restricted | Computer Graphics Forum Restricted | Computer Graphics Forum Restricted | Computer Graphics Forum Restricted | Computer Graphics Forum Restricted | Computer Graphics Forum Restricted | Computer Graphics Forum Restricted | Computer Graphics Forum Restricted


2019 Journal article Open Access OPEN

Volume-aware design of composite molds
Alderighi T., Malomo L., Giorgi D., Bickel B., Cignoni P. Pietroni N.
We propose a novel technique for the automatic design of molds to cast highly complex shapes. The technique generates composite, two-piece molds. Each mold piece is made up of a hard plastic shell and a flexible silicone part. Thanks to the thin, soft, and smartly shaped silicone part, which is kept in place by a hard plastic shell, we can cast objects of unprecedented complexity. An innovative algorithm based on a volumetric analysis defines the layout of the internal cuts in the silicone mold part. Our approach can robustly handle thin protruding features and intertwined topologies that have caused previous methods to fail. We compare our results with state of the art techniques, and we demonstrate the casting of shapes with extremely complex geometry.Source: ACM transactions on graphics 38 (2019). doi:10.1145/3306346.3322981
DOI: 10.1145/3306346.3322981
Project(s): EVOCATION via OpenAIRE, EMOTIVE via OpenAIRE, MATERIALIZABLE via OpenAIRE

See at: ISTI Repository Open Access | ACM Transactions on Graphics Open Access | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | CNR ExploRA Restricted | ACM Transactions on Graphics Restricted


2019 Report Restricted

A survey on 3D shape segmentation with focus on digital fabrication
Filoscia I., Alderighi T. Cignoni P., Giorgi D., Malomo L.
Segmenting 3D objects into parts is fundamental to a number of applications in computer graphics, including parametrization, texture mapping, shape matching, morphing, multi-resolution modeling, mesh editing, compression and animation [22]. Broadly speaking, shape segmentation techniques can be divided into geometry-based and semantics-based techniques. Geometry-based segmentations aim to partition the object into parts which have well-defined geometric properties such as size, curvature, or distance to a fitting primitive like a plane. Semantics-based segmentations, in turn, aim at identifying parts which are either visually relevant or meaningful in a given context, such as functional parts on mechanical objects or body parts on human models. Recently, 3D segmentation also drawn attention as a tool for efficient fabrication. The decomposition of objects into parts, indeed, helps solving different issues related to fabrication, such as height field constraints, volume constraints and need for supporting structures. In this work we present a complete survey of segmentation techniques, also highlighting their strengths and weaknesses. Our aim is to produce a handy overview to people who want to approach the problem of segmentation, especially if they want to apply it to digital fabrication.Source: ISTI Technical reports, 2019

See at: CNR ExploRA Restricted


2019 Report Restricted

A novel segmentation algorithm for support-free 3D printing
Filoscia I., Alderighi T., Cignoni P., Giorgi D., Malomo L.
Digital fabrication, and 3D printing in particular, are growing important in a variety of fields, from industry to medicine, from cultural heritage to art, as often they are more rapid and cheaper than traditional manufacturing techniques. In this context, our aim is to make it easier for people to print high-quality objects at home, even of complex shape, by incorporating into software some of the professional skills that are needed to fully exploit the potential of 3D printing A major limitation of FDM printers is that the material must be supported when it is deposited: bridge-like structures or hanging features, which are not supported by other object parts, often need additional support structures. Indeed, most printers can produce overhangs, but only up to a certain tolerance angle, usually in-between 30 and 60 degrees. To solve this problem, additional columns of material are built to support the parts in overhang. These supports need to be removed in a postprocessing step, which may cause imperfections on the surface, or even break thin parts. A possible solution, which we adopt in this work, is to segment the object into smaller parts which can be printed individually with no or minimal need for supports. The main drawback is that the decomposition introduces cuts on the object surface, in correspondence of the boundaries between parts. Such cuts can be as visually disturbing as the imperfections due to the removal of supports, or even more. Therefore, given a 3D mesh representing the input object, our aim is to develop a segmentation technique to partition the mesh into a small number of simpler parts, each of which can be printed with no or minimal support, and such that the boundaries between the parts (i.e., where the cuts in the object surface will be) affect the appearance of the printed model as little as possible. We pose the segmentation problem as a multi-labeling problem solved via functional minimization. In our formulation, the data points will be mesh elements (either faces or clusters of faces), and the labels will be potential printing directions. We will define an objective function that takes into account the area of supported regions and support footings, as well as the visual impact of the cuts, in terms of both their length and location on the surface. We formulate this multi-labeling problem as an Integer Linear Program (ILP), which can be solved using standard optimization packages such as Gurobi.Source: ISTI Technical reports, 2019

See at: CNR ExploRA Restricted


2019 Journal article Open Access OPEN

Towards a topological-geometrical theory of group equivariant non-expansive operators for data analysis and machine learning
Bergomi M. G., Frosini P., Giorgi D., Quercioli N.
We provide a general mathematical framework for group and set equivariance in machine learning. We define group equivariant non-expansive operators (GENEOs) as maps between function spaces associated with groups of transformations. We study the topological and metric properties of the space of GENEOs to evaluate their approximating power and set the basis for general strategies to initialize and compose operators. We define suitable pseudo-metrics for the function spaces, the equivariance groups and the set of non-expansive operators. We prove that, under suitable assumptions, the space of GENEOs is compact and convex. These results provide fundamental guarantees in a machine learning perspective. By considering isometry-equivariant non-expansive operators, we describe a simple strategy to select and sample operators. Thereafter, we show how selected and sampled operators can be used both to perform classical metric learning and to inject knowledge in artificial neural networks.Source: Nature Machine Intelligence 1 (2019): 423–433. doi:10.1038/s42256-019-0087-3
DOI: 10.1038/s42256-019-0087-3

See at: arXiv.org e-Print Archive Open Access | Nature Machine Intelligence Open Access | ISTI Repository Open Access | Nature Machine Intelligence Restricted | Nature Machine Intelligence Restricted | Nature Machine Intelligence Restricted | Nature Machine Intelligence Restricted | CNR ExploRA Restricted | Nature Machine Intelligence Restricted | Nature Machine Intelligence Restricted | Nature Machine Intelligence Restricted


2019 Contribution to conference Open Access OPEN

Computational fabrication of macromolecules to enhance perception and understanding of biological mechanisms
Alderighi T., Giorgi D., Malomo L., Cignoni P., Zoppè M.
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.Source: Smart Tools and Applications in Graphics (STAG) 2019, pp. 103–104, Cagliari, Italy, 14-15/11/2019
DOI: 10.2312/stag.20191369

See at: diglib.eg.org Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2018 Journal article Open Access OPEN

Computational topology to monitor human occupancy
Barsocchi P., Cassará P., Giorgi D., Moroni D., Pascali M. A.
The recent advances in sensing technologies, embedded systems, and wireless communication technologies, make it possible to develop smart systems to monitor human activities continuously. The occupancy of specific areas or rooms in a smart building is an important piece of information, to infer the behavior of people, or to trigger an advanced surveillancemodule. We propose a method based on computational topology to infer the occupancy of a room monitored for a week by a system of low-cost sensors.Source: Proceedings (MDPI) 2 (2018). doi:10.3390/proceedings2020099
DOI: 10.3390/proceedings2020099
DOI: 10.5281/zenodo.1159170
DOI: 10.5281/zenodo.1159169

See at: Proceedings Open Access | Proceedings Open Access | Proceedings Open Access | Proceedings Open Access | Proceedings Open Access | ZENODO Open Access | Hyper Article en Ligne Restricted | Hyper Article en Ligne Restricted | Hyper Article en Ligne Restricted | CNR ExploRA Restricted | www.mdpi.com Restricted


2018 Report Unknown

Metamolds: Computational design of silicone molds
Alderighi T., Malomo L., Giorgi D., Pietroni N., Bickel B., Cignoni P.
We propose a new method for fabricating digital objects through reusable silicone molds. Molds are generated by casting liquid silicone into custom 3D printed containers called metamolds. Metamolds automatically define the cuts that are needed to extract the cast object from the silicone mold. The shape of metamolds is designed through a novel segmentation technique, which takes into account both geometric and topological constraints involved in the process of mold casting. Our technique is simple, does not require to change the shape or topology of the input objects, and only requires off-the-shelf materials and technologies. We successfully tested our method on a set of challenging examples with complex shapes and rich geometric detail.Source: ISTI Technical reports, 2018
Project(s): EMOTIVE via OpenAIRE

See at: CNR ExploRA


2018 Journal article Open Access OPEN

Metamolds: computational design of silicone molds
Alderighi T., Malomo L., Giorgi D., Pietroni N., Bickel B., Cignoni P.
We propose a new method for fabricating digital objects through reusable silicone molds. Molds are generated by casting liquid silicone into custom 3D printed containers called metamolds. Metamolds automatically define the cuts that are needed to extract the cast object from the silicone mold. The shape of metamolds is designed through a novel segmentation technique, which takes into account both geometric and topological constraints involved in the process of mold casting. Our technique is simple, does not require changing the shape or topology of the input objects, and only requires off-the-shelf materials and technologies. We successfully tested our method on a set of challenging examples with complex shapes and rich geometric detailSource: ACM transactions on graphics 37 (2018): 136:1–136:13. doi:10.1145/3197517.3201381
DOI: 10.1145/3197517.3201381
Project(s): EMOTIVE via OpenAIRE

See at: ISTI Repository Open Access | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | CNR ExploRA Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted


2018 Contribution to book Open Access OPEN

Computer Vision for Ambient Assisted Living: Monitoring Systems for Personalized Healthcare and Wellness That Are Robust in the Real World and Accepted by Users, Carers, and Society
Colantonio S., Coppini G., Giorgi D., Morales M. A., Pascali M. A.
The Ambient Assisted Living (AAL) paradigm proposes advanced technologies and services to improve the quality of life, health, and wellbeing of citizens by making their daily-life activities easier and more secure, by monitoring patients under specific treatment, and by addressing at-risk subjects with proper counseling. The challenges brought by AAL range from robust, accurate, and nonintrusive data acquisition in dailylife settings to the development of services that are easy to use and appealing to the users and that support long-term engagement. This chapter offers a brief survey of existing vision-based monitoring solutions for personalized healthcare and wellness, and introduces the Wize Mirror, a multisensory platform featuring advanced algorithms fo cardiometabolic risk prevention and quality-of-life improvement.Source: Computer Vision for assistive Healthcare, edited by Marco Leo, Giovanni M. Farinella, pp. 147–182, 2018
DOI: 10.1016/b978-0-12-813445-0.00006-x

See at: ISTI Repository Open Access | academic.microsoft.com Restricted | api.elsevier.com Restricted | api.elsevier.com Restricted | CNR ExploRA Restricted | www.sciencedirect.com Restricted | www.sciencedirect.com Restricted


2017 Journal article Open Access OPEN

Persistent homology to analyse 3D faces and assess body weight gain
Giorgi D., Pascali M. A., Henriquez P., Matuszewski B. J., Colantonio S., Salvetti O.
In this paper, we analyse patterns in face shape variation due to weight gain. We propose the use of persistent homology descriptors to get geometric and topological information about the configuration of anthropometric 3D face landmarks. In this way, evaluating face changes boils down to comparing the descriptors computed on 3D face scans taken at different times. By applying dimensionality reduction techniques to the dissimilarity matrix of descriptors, we get a space in which each face is a point and face shape variations are encoded as trajectories in that space. Our results show that persistent homology is able to identify features which are well related to overweight and may help assessing individual weight trends. The research was carried out in the context of the European project SEMEOTICONS, which developed a multisensory platform which detects and monitors over time facial signs of cardio-metabolic risk.Source: The visual computer 33 (2017): 549–563. doi:10.1007/s00371-016-1344-7
DOI: 10.1007/s00371-016-1344-7
Project(s): SEMEOTICONS via OpenAIRE

See at: Central Lancashire Online Knowledge Open Access | ISTI Repository Open Access | The Visual Computer Restricted | The Visual Computer Restricted | The Visual Computer Restricted | link.springer.com Restricted | The Visual Computer Restricted | The Visual Computer Restricted | The Visual Computer Restricted | CNR ExploRA Restricted


2017 Journal article Open Access OPEN

Lip segmentation based on Lambertian shadings and morphological operators for hyper-spectral images
Danielis A., Giorgi D., Larsson M., Stromberg T., Colantonio S., Salvetti O.
Lip segmentation is a non-trivial task because the colour difference between the lip and the skin regions maybe not so noticeable sometimes. We propose an automatic lip segmentation technique for hyper-spectral images from an imaging prototype with medical applications. Contrarily to many other existing lip segmentation methods, we do not use colour space transformations to localise the lip area. As input image, we use for the first time a parametric blood concentration map computed by using narrow spectral bands. Our method mainly consists of three phases: (i) for each subject generate a subset of face images enhanced by different simulated Lambertian illuminations, then (ii) perform lip segmentation on each enhanced image by using constrained morphological operations, and finally (iii) extract features from Fourier-based modeled lip boundaries for selecting the lip candidate. Experiments for testing our approach are performed under controlled conditions on volunteers and on a public hyper-spectral dataset. Results show the effectiveness of the algorithm against low spectral range, moustache, and noise.Source: Pattern recognition 63 (2017): 355–370. doi:10.1016/j.patcog.2016.10.007
DOI: 10.1016/j.patcog.2016.10.007
Project(s): SEMEOTICONS via OpenAIRE

See at: ISTI Repository Open Access | Pattern Recognition Restricted | Pattern Recognition Restricted | Pattern Recognition Restricted | Pattern Recognition Restricted | CNR ExploRA Restricted | Pattern Recognition Restricted | Pattern Recognition Restricted


2017 Journal article Open Access OPEN

Mirror Mirror on the Wall ... An Unobtrusive Intelligent Multisensory Mirror for Well-Being Status Self-Assessment and Visualization
Henriquez P., Matuszewski B. J., Andreu-cabedo Y., Bastiani L., Colantonio S., Coppini G., D'Acunto M., Favilla R., Germanese D., Giorgi D., Marraccini P., Martinelli M., Morales M. A., Pascali M. A, Righi M., Salvetti O., Larsson M., Stromberg T., Randeberg L., Bjorgan A., Giannakakis G., Pediaditis M., Chiarugi F., Christinaki E., Marias K., Tsiknakis M.
A person's well-being status is reflected by their face through a combination of facial expressions and physical signs. The SEMEOTICONS project translates the semeiotic code of the human face into measurements and computational descriptors that are automatically extracted from images, videos, and three-dimensional scans of the face. SEMEOTICONS developed a multisensory platform in the form of a smart mirror to identify signs related to cardio-metabolic risk. The aim was to enable users to self-monitor their well-being status over time and guide them to improve their lifestyle. Significant scientific and technological challenges have been addressed to build the multisensory mirror, from touchless data acquisition, to real-time processing and integration of multimodal data.Source: IEEE transactions on multimedia 19 (2017): 1467–1481. doi:10.1109/TMM.2017.2666545
DOI: 10.1109/tmm.2017.2666545
Project(s): SEMEOTICONS via OpenAIRE

See at: IEEE Transactions on Multimedia Open Access | ISTI Repository Open Access | IEEE Transactions on Multimedia Restricted | IEEE Transactions on Multimedia Restricted | IEEE Transactions on Multimedia Restricted | IEEE Transactions on Multimedia Restricted | IEEE Transactions on Multimedia Restricted | IEEE Transactions on Multimedia Restricted | CNR ExploRA Restricted | IEEE Transactions on Multimedia Restricted | IEEE Transactions on Multimedia Restricted


2017 Report Restricted

Computational topology to monitor human occupancy
Barsocchi P., Cassarà P., Giorgi D., Moroni D., Pascali M. A.
The recent advances in sensing technologies, embedded sys- tems, and wireless communication technologies, make it pos- sible to develop smart systems to monitor human activities continuously. The occupancy of specific areas or rooms in a smart building is an important piece of information, to infer the behavior of people, or to trigger an advanced surveillance module. We propose a method based on computational topol- ogy to infer the occupancy of a room monitored for a week by a system of low-cost sensors.Source: ISTI Working papers, 2017

See at: CNR ExploRA Restricted


2017 Journal article Open Access OPEN

Lip segmentation on hyper-spectral images
Danielis A., Giorgi D., Colantonio S.
We present a lip segmentation method based on simulated Lambertian shadings. The input consists of hyper-spectral images generated by a prototype for medical applications.Source: ERCIM news (2017): 40–41.
Project(s): SEMEOTICONS via OpenAIRE

See at: ISTI Repository Open Access | ercim-news.ercim.eu Restricted | CNR ExploRA Restricted


2016 Journal article Open Access OPEN

Retrieval and classification methods for textured 3D models: a comparative study
Biasotti S. M., Cerri A., Aono M., Hamza A. B., Garro V., Giachetti A., Giorgi D., Godil A. A., Li G. C., Sanada C., Spagnuolo M., Tatsuma A., Velasco Forero S.
This paper presents a comparative study of six methods for the retrieval and classification of textured 3D models, which have been selected as representative of the state of the art. To better analyse and control how methods deal with specific classes of geometric and texture deformations, we built a collection of 572 synthetic textured mesh models, in which each class includes multiple texture and geometric modifications of a small set of null models. Results show a challenging, yet lively, scenario and also reveal interesting insights into how to deal with texture information according to different approaches, possibly working in the CIELab as well as in modifications of the RGB colour space.Source: The visual computer 32 (2016): 217–241. doi:10.1007/s00371-015-1146-3
DOI: 10.1007/s00371-015-1146-3
Project(s): IQMULUS via OpenAIRE, VISIONAIR via OpenAIRE

See at: The Visual Computer Open Access | ISTI Repository Open Access | The Visual Computer Restricted | The Visual Computer Restricted | The Visual Computer Restricted | Hal-Diderot Restricted | Hal-Diderot Restricted | Hal-Diderot Restricted | The Visual Computer Restricted | link.springer.com Restricted | The Visual Computer Restricted | The Visual Computer Restricted | The Visual Computer Restricted | The Visual Computer Restricted | CNR ExploRA Restricted


2016 Journal article Open Access OPEN

Wize Mirror - a smart, multisensory cardio-metabolic risk monitoring system
Andreu Y., Chiarugi F., Colantonio S., Giannakakis G., Giorgi D., Henriquez P., Kazantzaki E., Manousos D., Kostas M., Matuszewski B. J., Pascali M. A., Pediaditis M., Raccichini G., Tsiknakis M.
In the recent years personal health monitoring systems have been gaining popularity, both as a result of the pull from the general population, keen to improve well-being and early detection of possibly serious health conditions and the push from the industry eager to translate the current significant progress in computer vision and machine learning into commercial products. One of such systems is the Wize Mirror, built as a result of the FP7 funded SEMEOTICONS (SEMEiotic Oriented Technology for Individuals CardiOmetabolic risk self-assessmeNt and Self-monitoring) project. The project aims to translate the semeiotic code of the human face into computational descriptors and measures, automatically extracted from videos, multispectral images, and 3D scans of the face. The multisensory platform, being developed as the result of that project, in the form of a smart mirror, looks for signs related to cardio-metabolic risks. The goal is to enable users to self-monitor their well-being status over time and improve their life-style via tailored user guidance. This paper is focused on the description of the part of that system, utilising computer vision and machine learning techniques to perform 3D morphological analysis of the face and recognition of psycho-somatic status both linked with cardio-metabolic risks. The paper describes the concepts, methods and the developed implementations as well as reports on the results obtained on both real and synthetic datasets.Source: Computer vision and image understanding (Print) 148 (2016): 3–22. doi:10.1016/j.cviu.2016.03.018
DOI: 10.1016/j.cviu.2016.03.018
Project(s): SEMEOTICONS via OpenAIRE

See at: Central Lancashire Online Knowledge Open Access | Computer Vision and Image Understanding Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | www.sciencedirect.com Open Access | Computer Vision and Image Understanding Restricted | Computer Vision and Image Understanding Restricted | Computer Vision and Image Understanding Restricted | Computer Vision and Image Understanding Restricted | Computer Vision and Image Understanding Restricted | Computer Vision and Image Understanding Restricted | Computer Vision and Image Understanding Restricted | Computer Vision and Image Understanding Restricted


2016 Conference article Restricted

3D objects exploration: guidelines for future research
Biasotti S., Falcidieno B., Giorgi D., Spagnuolo M.
Search engines provide the interface to interact with 3D object repositories, which are rapidly growing in both number and size. This position paper presents the current state of the art on 3D dataset navigation and 3D model retrieval. We discuss a number of challenges we consider as the main points to be tackled for developing effective 3D object exploration systems.Source: Eurographics Workshop on 3D Object Retrieval, pp. 9–12, Lisbona, Portugal, 8 May 2016
DOI: 10.2312/3dor.20161081

See at: diglib.eg.org Restricted | CNR ExploRA Restricted