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2018
Conference article
Open Access
Simplification of shapes for fabrication with V-groove milling tools
Muntoni A, Scalas A, Nuvoli S, Scateni R
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.DOI: 10.2312/stag.20181293
Metrics:
Muntoni A, Scalas A, Nuvoli S, Scateni R
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.DOI: 10.2312/stag.20181293
Metrics:
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diglib.eg.org 
| CNR IRIS | ISTI Repository | hdl.handle.net 
| CNR IRIS
2018
Journal article
Open Access
Fabrication oriented shape decomposition using polycube mapping
Fanni Fa, Cherchi G, Muntoni A, Tola A, Scateni R
In recent years, fabrication technologies have developed at a breakneck pace. However, some limitations on shape and dimension still apply both to additive and subtractive manufacturing, and one way to bypass them could be the partition of the object to build. We present here a novel algorithm, based on the polycube representation of the original shape, able to decompose any model into smaller parts simpler to fabricate. We first map the shape in a polycube and, then, split it to take advantage of the polycube partitioning. In this way, we obtain quite easily a partition of the model. In this work we also study and analyze pros and cons of this partitioning scheme for fabrication, when using both the additive and subtractive pipelines. Our proposed partitioning scheme is computationally light, and it produces high-grade results, especially when applied to models that we can map onto polycubes with a high compactness value.Source: COMPUTERS & GRAPHICS, vol. 77, pp. 183-193
DOI: 10.1016/j.cag.2018.10.010
Metrics:
Fanni Fa, Cherchi G, Muntoni A, Tola A, Scateni R
In recent years, fabrication technologies have developed at a breakneck pace. However, some limitations on shape and dimension still apply both to additive and subtractive manufacturing, and one way to bypass them could be the partition of the object to build. We present here a novel algorithm, based on the polycube representation of the original shape, able to decompose any model into smaller parts simpler to fabricate. We first map the shape in a polycube and, then, split it to take advantage of the polycube partitioning. In this way, we obtain quite easily a partition of the model. In this work we also study and analyze pros and cons of this partitioning scheme for fabrication, when using both the additive and subtractive pipelines. Our proposed partitioning scheme is computationally light, and it produces high-grade results, especially when applied to models that we can map onto polycubes with a high compactness value.Source: COMPUTERS & GRAPHICS, vol. 77, pp. 183-193
DOI: 10.1016/j.cag.2018.10.010
Metrics:
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Computers & Graphics | Computers & Graphics | CNR IRIS | CNR IRIS | www.sciencedirect.com
2019
Conference article
Unknown
Split and mill: user assisted height-field block decomposition for fabrication
Muntoni A, Spano Ld, Scateni R
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.DOI: 10.2312/stag.20191364
Metrics:
Muntoni A, Spano Ld, Scateni R
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.DOI: 10.2312/stag.20191364
Metrics:
See at:
diglib.eg.org | CNR IRIS
2021
Journal article
Open Access
Automatic surface segmentation for seamless fabrication using 4-axis milling machines
Nuvoli S., Tola A., Muntoni A., Pietroni N., Gobbetti E., Scateni R.
We introduce a novel geometry-processing pipeline to guide the fabrication of complex shapes from a single block of material using 4-axis CNC milling machines. This setup extends classical 3-axis CNC machining with an extra degree of freedom to rotate the object around a fixed axis. The first step of our pipeline identifies the rotation axis that maximizes the overall fabrication accuracy. Then we identify two height-field regions at the rotation axis's extremes used to secure the block on the rotation tool. We segment the remaining portion of the mesh into a set of height-fields whose principal directions are orthogonal to the rotation axis. The segmentation balances the approximation quality, the boundary smoothness, and the total number of patches. Additionally, the segmentation process takes into account the object's geometric features, as well as saliency information. The output is a set of meshes ready to be processed by off-the-shelf software for the 3-axis tool-path generation. We present several results to demonstrate the quality and efficiency of our approach to a range of inputs.Source: COMPUTER GRAPHICS FORUM (ONLINE), vol. 40 (issue 2)
DOI: 10.1111/cgf.142625
Metrics:
Nuvoli S., Tola A., Muntoni A., Pietroni N., Gobbetti E., Scateni R.
We introduce a novel geometry-processing pipeline to guide the fabrication of complex shapes from a single block of material using 4-axis CNC milling machines. This setup extends classical 3-axis CNC machining with an extra degree of freedom to rotate the object around a fixed axis. The first step of our pipeline identifies the rotation axis that maximizes the overall fabrication accuracy. Then we identify two height-field regions at the rotation axis's extremes used to secure the block on the rotation tool. We segment the remaining portion of the mesh into a set of height-fields whose principal directions are orthogonal to the rotation axis. The segmentation balances the approximation quality, the boundary smoothness, and the total number of patches. Additionally, the segmentation process takes into account the object's geometric features, as well as saliency information. The output is a set of meshes ready to be processed by off-the-shelf software for the 3-axis tool-path generation. We present several results to demonstrate the quality and efficiency of our approach to a range of inputs.Source: COMPUTER GRAPHICS FORUM (ONLINE), vol. 40 (issue 2)
DOI: 10.1111/cgf.142625
Metrics:
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IRIS Cnr | Archivio istituzionale della ricerca - Università di Cagliari | Archivio istituzionale della ricerca - Università di Cagliari | IRIS Cnr | Computer Graphics Forum | Computer Graphics Forum | Computer Graphics Forum | CNR IRIS
2019
Journal article
Open Access
Mill and fold: shape simplification for fabrication
Muntoni A, Nuvoli S, Scalas A, Tola A, Malomo L, Scateni R
We introduce a pipeline for simplifying digital 3D shapes and fabricate 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 create 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, which consists only in folding adjacent facets at a constrained angle. 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 simplified version of the input model, using the marching cubes algorithm on the original mesh and iteratively performing local changes on the resulting triangle mesh. The user can then perform an additional manual simplification to remove unwanted facets. Finally, an unfolding algorithm, which takes into account the thickness of the material, flattens the polygonal facets onto the 2D plane, so that a CNC milling machine can fabricate it from a sheet of rigid material.Source: COMPUTERS & GRAPHICS, vol. 80, pp. 17-28
DOI: 10.1016/j.cag.2019.03.003
Metrics:
Muntoni A, Nuvoli S, Scalas A, Tola A, Malomo L, Scateni R
We introduce a pipeline for simplifying digital 3D shapes and fabricate 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 create 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, which consists only in folding adjacent facets at a constrained angle. 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 simplified version of the input model, using the marching cubes algorithm on the original mesh and iteratively performing local changes on the resulting triangle mesh. The user can then perform an additional manual simplification to remove unwanted facets. Finally, an unfolding algorithm, which takes into account the thickness of the material, flattens the polygonal facets onto the 2D plane, so that a CNC milling machine can fabricate it from a sheet of rigid material.Source: COMPUTERS & GRAPHICS, vol. 80, pp. 17-28
DOI: 10.1016/j.cag.2019.03.003
Metrics:
See at:
CNR IRIS | ISTI Repository | www.sciencedirect.com | Computers & Graphics | CNR IRIS | CNR IRIS
2021
Software
Metadata Only Access
MeshLab 2021.07
Muntoni A, Cignoni P
MeshLab is an open source, portable, and extensible system for the processing and editing of unstructured large 3D triangular meshes. It is aimed to help the processing of the typical not-so-small unstructured models arising in 3D scanning, providing a set of tools for editing, cleaning, healing, inspecting, rendering and converting this kind of meshes.
Muntoni A, Cignoni P
MeshLab is an open source, portable, and extensible system for the processing and editing of unstructured large 3D triangular meshes. It is aimed to help the processing of the typical not-so-small unstructured models arising in 3D scanning, providing a set of tools for editing, cleaning, healing, inspecting, rendering and converting this kind of meshes.
See at:
CNR IRIS | www.meshlab.net
2021
Software
Metadata Only Access
PyMeshLab 2021.07
Muntoni A, Cignoni P
PyMeshLab is a Python library that interfaces to MeshLab, the popular open source application for editing and processing large 3D triangle meshes.
Muntoni A, Cignoni P
PyMeshLab is a Python library that interfaces to MeshLab, the popular open source application for editing and processing large 3D triangle meshes.
See at:
CNR IRIS | pymeshlab.readthedocs.io
2020
Software
Metadata Only Access
MeshLab 2020.12
Muntoni A, Cignoni P
MeshLab is an open source, portable, and extensible system for the processing and editing of unstructured large 3D triangular meshes. It is aimed to help the processing of the typical not-so-small unstructured models arising in 3D scanning, providing a set of tools for editing, cleaning, healing, inspecting, rendering and converting this kind of meshes.
Muntoni A, Cignoni P
MeshLab is an open source, portable, and extensible system for the processing and editing of unstructured large 3D triangular meshes. It is aimed to help the processing of the typical not-so-small unstructured models arising in 3D scanning, providing a set of tools for editing, cleaning, healing, inspecting, rendering and converting this kind of meshes.
See at:
CNR IRIS | www.meshlab.net
2021
Software
Open Access
PyMeshLab
Muntoni A., Cignoni P.
PyMeshLab is a Python library that interfaces to MeshLab, the popular open source application for editing and processing large 3D triangle meshes. Python bindings are generated using pybind11.DOI: 10.5281/zenodo.4438750
Metrics:
Muntoni A., Cignoni P.
PyMeshLab is a Python library that interfaces to MeshLab, the popular open source application for editing and processing large 3D triangle meshes. Python bindings are generated using pybind11.DOI: 10.5281/zenodo.4438750
Metrics:
See at:
CNR IRIS | pymeshlab.readthedocs.io | CNR IRIS
2024
Software
Open Access
PyMeshLab 2023.12.post2
Muntoni A., Cignoni P.
PyMeshLab is a Python library that interfaces to MeshLab, the popular open source application for editing and processing large 3D triangle meshes. Python bindings are generated using pybind11.DOI: 10.5281/zenodo.13768931
Metrics:
Muntoni A., Cignoni P.
PyMeshLab is a Python library that interfaces to MeshLab, the popular open source application for editing and processing large 3D triangle meshes. Python bindings are generated using pybind11.DOI: 10.5281/zenodo.13768931
Metrics:
See at:
CNR IRIS | pymeshlab.readthedocs.io | CNR IRIS
2020
Software
Open Access
MeshLab
Muntoni A., Callieri M., Corsini M., Cignoni P.
MeshLab is an open source, portable, and extensible system for the processing and editing of unstructured large 3D triangular meshes. It is aimed to help the processing of the typical not-so-small unstructured models arising in 3D scanning, providing a set of tools for editing, cleaning, healing, inspecting, rendering and converting this kind of meshes.DOI: 10.5281/zenodo.5114037
Metrics:
Muntoni A., Callieri M., Corsini M., Cignoni P.
MeshLab is an open source, portable, and extensible system for the processing and editing of unstructured large 3D triangular meshes. It is aimed to help the processing of the typical not-so-small unstructured models arising in 3D scanning, providing a set of tools for editing, cleaning, healing, inspecting, rendering and converting this kind of meshes.DOI: 10.5281/zenodo.5114037
Metrics:
See at:
CNR IRIS | www.meshlab.net | CNR IRIS
2023
Software
Open Access
MeshLab 2023.12
Muntoni A., Callieri M., Corsini M., Cignoni P.
MeshLab is an open source, portable, and extensible system for the processing and editing of unstructured large 3D triangular meshes. It is aimed to help the processing of the typical not-so-small unstructured models arising in 3D scanning, providing a set of tools for editing, cleaning, healing, inspecting, rendering and converting this kind of meshes.DOI: 10.5281/zenodo.10362278
Metrics:
Muntoni A., Callieri M., Corsini M., Cignoni P.
MeshLab is an open source, portable, and extensible system for the processing and editing of unstructured large 3D triangular meshes. It is aimed to help the processing of the typical not-so-small unstructured models arising in 3D scanning, providing a set of tools for editing, cleaning, healing, inspecting, rendering and converting this kind of meshes.DOI: 10.5281/zenodo.10362278
Metrics:
See at:
CNR IRIS | www.meshlab.net | CNR IRIS
2024
Software
Open Access
RelightLab 2024.11
Ponchio F., Potenziani M., Muntoni A., Cignoni P.
Relight is a library to create and view (on the web) relightable images (RTI), It supports Polinomial Texture Mapping (PTM), Hemispherical Harmonics (HSH) along with a new Principal Component Analysis (PCA) + Radial Basis Function (RBF) based algorithm with better fidelity (for the same cost and space). It also supports RTI (and image) streamed tiled viewing based on DeepZoom, Google, Zoomify, IIP formats.DOI: 10.5281/zenodo.14196912
Metrics:
Ponchio F., Potenziani M., Muntoni A., Cignoni P.
Relight is a library to create and view (on the web) relightable images (RTI), It supports Polinomial Texture Mapping (PTM), Hemispherical Harmonics (HSH) along with a new Principal Component Analysis (PCA) + Radial Basis Function (RBF) based algorithm with better fidelity (for the same cost and space). It also supports RTI (and image) streamed tiled viewing based on DeepZoom, Google, Zoomify, IIP formats.DOI: 10.5281/zenodo.14196912
Metrics:
See at:
CNR IRIS | vcg.isti.cnr.it | CNR IRIS
2022
Journal article
Open Access
TagLab: AI-assisted annotation for the fast and accurate semantic segmentation of coral reef orthoimages
Pavoni G, Corsini M, Ponchio F, Muntoni A, Edwards C, Pedersen N, Sandin S, Cignoni P
Semantic segmentation is a widespread image analysis task; in some applications, it requires such high accuracy that it still has to be done manually, taking a long time. Deep learning-based approaches can significantly reduce such times, but current automated solutions may produce results below expert standards. We propose agLab, an interactive tool for the rapid labelling and analysis of orthoimages that speeds up semantic segmentation. TagLab follows a human-centered artificial intelligence approach that, by integrating multiple degrees of automation, empowers human capabilities. We evaluated TagLab's efficiency in annotation time and accuracy through a user study based on a highly challenging task: the semantic segmentation of coral communities in marine ecology. In the assisted labelling of corals, TagLab increased the annotation speed by approximately 90% for nonexpert annotators while preserving the labelling accuracy. Furthermore, human-machine interaction has improved the accuracy of fully automatic predictions by about 7% on average and by 14% when the model generalizes poorly. Considering the experience done through the user study, TagLab has been improved, and preliminary investigations suggest a further significant reduction in annotation times.Source: JOURNAL OF FIELD ROBOTICS, vol. 39 (issue 3), pp. 246-262
DOI: 10.1002/rob.22049
Metrics:
Pavoni G, Corsini M, Ponchio F, Muntoni A, Edwards C, Pedersen N, Sandin S, Cignoni P
Semantic segmentation is a widespread image analysis task; in some applications, it requires such high accuracy that it still has to be done manually, taking a long time. Deep learning-based approaches can significantly reduce such times, but current automated solutions may produce results below expert standards. We propose agLab, an interactive tool for the rapid labelling and analysis of orthoimages that speeds up semantic segmentation. TagLab follows a human-centered artificial intelligence approach that, by integrating multiple degrees of automation, empowers human capabilities. We evaluated TagLab's efficiency in annotation time and accuracy through a user study based on a highly challenging task: the semantic segmentation of coral communities in marine ecology. In the assisted labelling of corals, TagLab increased the annotation speed by approximately 90% for nonexpert annotators while preserving the labelling accuracy. Furthermore, human-machine interaction has improved the accuracy of fully automatic predictions by about 7% on average and by 14% when the model generalizes poorly. Considering the experience done through the user study, TagLab has been improved, and preliminary investigations suggest a further significant reduction in annotation times.Source: JOURNAL OF FIELD ROBOTICS, vol. 39 (issue 3), pp. 246-262
DOI: 10.1002/rob.22049
Metrics:
See at:
CNR IRIS | onlinelibrary.wiley.com | CNR IRIS
2021
Conference article
Open Access
TagLab: A human-centric AI system for interactive semantic segmentation
Pavoni G, Corsini M, Ponchio F, Muntoni A, Cignoni P
Fully automatic semantic segmentation of highly specific semantic classes and complex shapes may not meet the accuracy standards demanded by scientists. In such cases, human-centered AI solutions, able to assist operators while preserving human control over complex tasks, are a good trade-off to speed up image labeling while maintaining high accuracy levels. TagLab is an open-source AI-assisted software for annotating large orthoimages which takes advantage of different degrees of automation; it speeds up image annotation from scratch through assisted tools, creates custom fully automatic semantic segmentation models, and, finally, allows the quick edits of automatic predictions. Since the orthoimages analysis applies to several scientific disciplines, TagLab has been designed with a flexible labeling pipeline. We report our results in two different scenarios, marine ecology, and architectural heritage.DOI: 10.48550/arxiv.2112.12702
Metrics:
Pavoni G, Corsini M, Ponchio F, Muntoni A, Cignoni P
Fully automatic semantic segmentation of highly specific semantic classes and complex shapes may not meet the accuracy standards demanded by scientists. In such cases, human-centered AI solutions, able to assist operators while preserving human control over complex tasks, are a good trade-off to speed up image labeling while maintaining high accuracy levels. TagLab is an open-source AI-assisted software for annotating large orthoimages which takes advantage of different degrees of automation; it speeds up image annotation from scratch through assisted tools, creates custom fully automatic semantic segmentation models, and, finally, allows the quick edits of automatic predictions. Since the orthoimages analysis applies to several scientific disciplines, TagLab has been designed with a flexible labeling pipeline. We report our results in two different scenarios, marine ecology, and architectural heritage.DOI: 10.48550/arxiv.2112.12702
Metrics:
See at:
arXiv.org e-Print Archive | CNR IRIS | ISTI Repository | doi.org | CNR IRIS
2023
Journal article
Open Access
Quantifying the loss of coral from a bleaching event using underwater photogrammetry and AI-Assisted Image Segmentation
Kopecky K. L., Pavoni G., Nocerino E., Brooks A. J., Corsini M., Menna F., Gallagher J. P., Capra A., Castagnetti C., Rossi P., Gruen A., Neyer F., Muntoni A., Ponchio F., Cignoni P., Troyer M., Holbrook S. J., Schmitt R. J.
Detecting the impacts of natural and anthropogenic disturbances that cause declines in organisms or changes in community composition has long been a focus of ecology. However, a tradeoff often exists between the spatial extent over which relevant data can be collected, and the resolution of those data. Recent advances in underwater photogrammetry, as well as computer vision and machine learning tools that employ artificial intelligence (AI), offer potential solutions with which to resolve this tradeoff. Here, we coupled a rigorous photogrammetric survey method with novel AI-assisted image segmentation software in order to quantify the impact of a coral bleaching event on a tropical reef, both at an ecologically meaningful spatial scale and with high spatial resolution. In addition to outlining our workflow, we highlight three key results: (1) dramatic changes in the three-dimensional surface areas of live and dead coral, as well as the ratio of live to dead colonies before and after bleaching; (2) a size-dependent pattern of mortality in bleached corals, where the largest corals were disproportionately affected, and (3) a significantly greater decline in the surface area of live coral, as revealed by our approximation of the 3D shape compared to the more standard planar area (2D) approach. The technique of photogrammetry allows us to turn 2D images into approximate 3D models in a flexible and efficient way. Increasing the resolution, accuracy, spatial extent, and efficiency with which we can quantify effects of disturbances will improve our ability to understand the ecological consequences that cascade from small to large scales, as well as allow more informed decisions to be made regarding the mitigation of undesired impacts.Source: REMOTE SENSING (BASEL), vol. 15 (issue 16)
DOI: 10.3390/rs15164077
Metrics:
Kopecky K. L., Pavoni G., Nocerino E., Brooks A. J., Corsini M., Menna F., Gallagher J. P., Capra A., Castagnetti C., Rossi P., Gruen A., Neyer F., Muntoni A., Ponchio F., Cignoni P., Troyer M., Holbrook S. J., Schmitt R. J.
Detecting the impacts of natural and anthropogenic disturbances that cause declines in organisms or changes in community composition has long been a focus of ecology. However, a tradeoff often exists between the spatial extent over which relevant data can be collected, and the resolution of those data. Recent advances in underwater photogrammetry, as well as computer vision and machine learning tools that employ artificial intelligence (AI), offer potential solutions with which to resolve this tradeoff. Here, we coupled a rigorous photogrammetric survey method with novel AI-assisted image segmentation software in order to quantify the impact of a coral bleaching event on a tropical reef, both at an ecologically meaningful spatial scale and with high spatial resolution. In addition to outlining our workflow, we highlight three key results: (1) dramatic changes in the three-dimensional surface areas of live and dead coral, as well as the ratio of live to dead colonies before and after bleaching; (2) a size-dependent pattern of mortality in bleached corals, where the largest corals were disproportionately affected, and (3) a significantly greater decline in the surface area of live coral, as revealed by our approximation of the 3D shape compared to the more standard planar area (2D) approach. The technique of photogrammetry allows us to turn 2D images into approximate 3D models in a flexible and efficient way. Increasing the resolution, accuracy, spatial extent, and efficiency with which we can quantify effects of disturbances will improve our ability to understand the ecological consequences that cascade from small to large scales, as well as allow more informed decisions to be made regarding the mitigation of undesired impacts.Source: REMOTE SENSING (BASEL), vol. 15 (issue 16)
DOI: 10.3390/rs15164077
Metrics:
See at:
CNR IRIS | ISTI Repository | www.mdpi.com | CNR IRIS
2024
Software
Restricted
TagLab 2024.12.2
Corsini M., Pavoni G., Ponchio F., Muntoni A., Saraceni Q., Cignoni P.
TagLab is an AI-powered segmentation software designed to support the analysis of large orthographic images generated through the photogrammetric pipeline.DOI: 10.5281/zenodo.14258304
Metrics:
Corsini M., Pavoni G., Ponchio F., Muntoni A., Saraceni Q., Cignoni P.
TagLab is an AI-powered segmentation software designed to support the analysis of large orthographic images generated through the photogrammetric pipeline.DOI: 10.5281/zenodo.14258304
Metrics:
See at:
CNR IRIS | CNR IRIS | taglab.isti.cnr.it
2022
Journal article
Open Access
Design and construction of a bending-active plywood structure: the Flexmaps Pavilion
Laccone F, Malomo L, Callieri M, Alderighi T, Muntoni A, Ponchio F, Pietroni N, Cignoni P
Mesostructured patterns are a modern and efficient concept based on designing the geometry of structural material at the meso-scale to achieve desired mechanical performances. In the context of bending-active structures, such a concept can be used to control the flexibility of the panels forming a surface without changing the constituting material. These panels undergo a formation process of deformation by bending, and application of internal restraints. This paper describes a new constructional system, FlexMaps, that has initiated the adoption of bending-active mesostructures at the architectural scale. Here, these modules are in the form of four-arms spirals made of CNC-milled plywood and are designed to reach the desired target shape once assembled. All phases from the conceptual design to the fabrication are seamlessly linked within an automated workflow. To illustrate the potential of the system, the paper discusses the results of a demonstrator project entitled FlexMaps Pavilion (3.90x3.96x3.25 meters) that has been exhibited at the IASS Symposium in 2019 and more recently at the 2021 17th International Architecture Exhibition, La Biennale di Venezia. The structural response is investigated through a detailed structural analysis, and the long-term behavior is assessed through a photogrammetric survey.Source: JOURNAL OF THE INTERNATIONAL ASSOCIATION FOR SHELL AND SPATIAL STRUCTURES, vol. 63 (issue 2), pp. 98-114
DOI: 10.20898/j.iass.2022.007
Metrics:
Laccone F, Malomo L, Callieri M, Alderighi T, Muntoni A, Ponchio F, Pietroni N, Cignoni P
Mesostructured patterns are a modern and efficient concept based on designing the geometry of structural material at the meso-scale to achieve desired mechanical performances. In the context of bending-active structures, such a concept can be used to control the flexibility of the panels forming a surface without changing the constituting material. These panels undergo a formation process of deformation by bending, and application of internal restraints. This paper describes a new constructional system, FlexMaps, that has initiated the adoption of bending-active mesostructures at the architectural scale. Here, these modules are in the form of four-arms spirals made of CNC-milled plywood and are designed to reach the desired target shape once assembled. All phases from the conceptual design to the fabrication are seamlessly linked within an automated workflow. To illustrate the potential of the system, the paper discusses the results of a demonstrator project entitled FlexMaps Pavilion (3.90x3.96x3.25 meters) that has been exhibited at the IASS Symposium in 2019 and more recently at the 2021 17th International Architecture Exhibition, La Biennale di Venezia. The structural response is investigated through a detailed structural analysis, and the long-term behavior is assessed through a photogrammetric survey.Source: JOURNAL OF THE INTERNATIONAL ASSOCIATION FOR SHELL AND SPATIAL STRUCTURES, vol. 63 (issue 2), pp. 98-114
DOI: 10.20898/j.iass.2022.007
Metrics:
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CNR IRIS | ISTI Repository | CNR IRIS | CNR IRIS | CNR IRIS
2017
Conference article
Open Access
A seamless pipeline for the acquisition of the body shape: the Virtuoso case study
Saba M., Sorrentino F., Muntoni A., Casti S., Cherchi G., Carcangiu A., Corda F., Murru A., Spano L. D., Scateni R., Vitali I., Salvetti O., Magrini M., Villa A., Carboni A., Pascali M. A.
In this paper, we describe the design and the implementation of the demonstrator for the Virtuoso project, which aims at creatingseamless support for fitness and wellness activities in touristic resort. We define the objectives of the user interface, the hardwareand software setup, showing how we combined and exploited consumer-level devices for supporting 3D body scan, contact-lessacquisition of physical parameters, exercise guidance and operator support.DOI: 10.2312/stag.20171229
Metrics:
Saba M., Sorrentino F., Muntoni A., Casti S., Cherchi G., Carcangiu A., Corda F., Murru A., Spano L. D., Scateni R., Vitali I., Salvetti O., Magrini M., Villa A., Carboni A., Pascali M. A.
In this paper, we describe the design and the implementation of the demonstrator for the Virtuoso project, which aims at creatingseamless support for fitness and wellness activities in touristic resort. We define the objectives of the user interface, the hardwareand software setup, showing how we combined and exploited consumer-level devices for supporting 3D body scan, contact-lessacquisition of physical parameters, exercise guidance and operator support.DOI: 10.2312/stag.20171229
Metrics:
See at:
IRIS Cnr | IRIS Cnr | IRIS Cnr | diglib.eg.org | Archivio istituzionale della ricerca - Università di Cagliari | Archivio istituzionale della ricerca - Università di Cagliari | CNR IRIS