288 result(s)
Page Size: 10, 20, 50
Export: bibtex, xml, json, csv
Order by:

CNR Author operator: and / or
more
Typology operator: and / or
Language operator: and / or
Date operator: and / or
more
Rights operator: and / or
2021 Contribution to book Open Access OPEN

Documentazione digitale avanzata in emergenza
Cignoni P.
Il contributo descrive la campagna di acquisizione condotta nel maggio 2020 in seguito al ritrovamento di una serie di sepolture di epoca romana durante alcuni scavi per manutenzione delle condotte idriche.Source: Emergenze etrusche e romane nell'anno del Covid-19, edited by Andrea Camilli, Carolina Megali, pp. 76–79. Pisa: Pacini Editore, 2021

See at: ISTI Repository Open Access | CNR ExploRA Restricted


2021 Journal article Open Access OPEN

Texture Defragmentation for Photo-Reconstructed 3D Models
Maggiordomo A, Cignoni P., Tarini M.
We propose a method to improve an existing parametrization (UV-map layout) of a textured 3D model, targeted explicitly at alleviating typical defects afflicting models generated with automatic photo-reconstruction tools from real-world objects. This class of 3D data is becoming increasingly important thanks to the growing popularity of reliable, ready-to-use photogrammetry software packages. The resulting textured models are richly detailed, but their underlying parametrization typically falls short of many practical requirements, particularly exhibiting excessive fragmentation and consequent problems. Producing a completely new UV-map, with standard parametrization techniques, and then resampling a new texture image, is often neither practical nor desirable for at least two reasons: first, these models have characteristics (such as inconsistencies, high resolution) that make them unfit for automatic or manual parametrization; second, the required resampling leads to unnecessary signal degradation because this process is unaware of the original texel densities. In contrast, our method improves the existing UV-map instead of replacing it, balancing the reduction of the map fragmentation with signal degradation due to resampling, while also avoiding oversampling of the original signal. The proposed approach is fully automatic and extensively tested on a large benchmark of photo-reconstructed models; quantitative evaluation evidences a drastic and consistent improvement of the mappingsSource: Computer graphics forum (Online) 40 (2021): 65–78. doi:10.1111/cgf.142615
DOI: 10.1111/cgf.142615
Project(s): ARIADNEplus via OpenAIRE

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


2021 Conference article Open Access OPEN

Collaborative Visual Environments for Evidence Taking in Digital Justice: a Design Concept
Erra U., Capece N., Lettieri N., Fabiani E., Banterle F., Cignoni P., Dazzi P., Aleotti J., Monica R.
In recent years, Spatial Computing (SC) has emerged as a novel paradigm thanks to the advancements in Extended Reality (XR), remote sensing, and artificial intelligence. Computers are nowadays more and more aware of physical environments (i.e. objects shape, size, location and movement) and can use this knowledge to blend technology into reality seamlessly, merge digital and real worlds, and connect users by providing innovative interaction methods. Criminal and civil trials offer an ideal scenario to exploit Spatial Computing. The taking of evidence, indeed, is a complex activity that not only involves several actors (judges, lawyers, clerks, advi- sors) but it often requires accurate topographic surveys of places and objects. Moreover, another essential means of proof, the "judi- cial experiments" - reproductions of real-world events (e.g. a road accident) the judge uses to evaluate if and how a given fact has taken place - could be usefully carried out in virtual environments. In this paper we propose a novel approach for digital justice based on a multi-user, multimodal virtual collaboration platform that enables technology-enhanced acquisition and analysis of trial evidence.Source: FRAME'21 - 1st Workshop on Flexible Resource and Application Management on the Edge, Sweden, Virtual Event, 25/06/2021
DOI: 10.1145/3452369.3463820
Project(s): ACCORDION via OpenAIRE

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2021 Journal article Open Access OPEN

Augmented virtuality using touch-sensitive 3D-printed objects
Palma G., Perry S., Cignoni P.
Virtual reality (VR) technologies have become more and more affordable and popular in the last five years thanks to hardware and software advancements. A critical issue for these technologies is finding paradigms that allow user interactions in ways that are as similar as possible to the real world, bringing physicality into the experience. Current literature has shown, with different experiments, that the mapping of real objects in virtual reality alongside haptic feedback significantly increases the realism of the experience and user engagement, leading to augmented virtuality. In this paper, we present a system to improve engagement in a VR experience using inexpensive, physical, and sensorized copies of real artefacts made with cheap 3D fabrication technologies. Based on a combination of hardware and software components, the proposed system gives the user the possibility to interact with the physical replica in the virtual environment and to see the appearance of the original cultural heritage artefact. In this way, we overcome one of the main limitations of mainstream 3D fabrication technologies: a faithful appearance reproduction. Using a consumer device for the real-time hand tracking and a custom electronic controller for the capacitive touch sensing, the system permits the creation of augmented experiences where the user with their hands can change the virtual appearance of the real replica object using a set of personalization actions selectable from a physical 3D-printed palette.Source: Remote sensing (Basel) 13 (2021). doi:10.3390/rs13112186
DOI: 10.3390/rs13112186
Project(s): EMOTIVE via OpenAIRE

See at: ISTI Repository Open Access | CNR ExploRA Open Access | www.mdpi.com Open Access


2021 Journal article Open Access OPEN

Integrated computational framework for the design and fabrication of bending-active structures made from flat sheet materiall
Laccone F., Malomo L., Pietroni N., Cignoni P., Schork T.
This paper introduces an integrated computational design framework for the design and realization of arbitrarily-curved bending-active architectural structures. The developed framework consists of a series of methods that enable the production of a complex 3D structures composed of a set of flat 2D panels whose mechanical properties are locally tuned by varying the shape of embedded spiraling patterns. The resulting panels perform as variable stiffness elements, and they are optimized to match a desired target shape once assembled together. The presented framework includes all the steps for the physical delivery of architectural objects, including conception, static assessment, and digital fabrication. The developed framework has been applied to an architectural scale prototype, which demonstrates the potential of integrating architectural design, computational simulation, structural engineering, and digital fabrication, opening up several possible novel applications in the building sector.Source: Structures (Oxford) 34 (2021): 979–994. doi:10.1016/j.istruc.2021.08.004
DOI: 10.1016/j.istruc.2021.08.004

See at: ISTI Repository Open Access | CNR ExploRA Restricted | www.sciencedirect.com Restricted


2021 Software Unknown

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.

See at: CNR ExploRA | www.meshlab.net


2021 Software Unknown

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.

See at: CNR ExploRA | pymeshlab.readthedocs.io


2021 Journal article Restricted

Volume decomposition for two-piece rigid casting
Alderighi T., Malomo L., Bickel B., Cignoni P., Pietroni N.
We introduce a novel technique to automatically decompose an input object's volume into a set of parts that can be represented by two opposite height fields. Such decomposition enables the manufacturing of individual parts using two-piece reusable rigid molds. Our decomposition strategy relies on a new energy formulation that utilizes a pre-computed signal on the mesh volume representing the accessibility for a predefined set of extraction directions. Thanks to this novel formulation, our method allows for efficient optimization of a fabrication-aware partitioning of volumes in a completely automatic way. We demonstrate the efficacy of our approach by generating valid volume partitionings for a wide range of complex objects and physically reproducing several of them.Source: ACM transactions on graphics 40 (2021). doi:10.1145/3478513.3480555
DOI: 10.1145/3478513.3480555
Project(s): MATERIALIZABLE via OpenAIRE

See at: CNR ExploRA Restricted


2020 Journal article Open Access OPEN

A State of the Art Technology in Large Scale Underwater Monitoring
Pavoni G., Corsini M., Cignoni P.
In recent decades, benthic populations have been subjected to recurrent episodes of mass mortality. These events have been blamed in part on declining water quality and elevated water temperatures (see Figure 1) correlated to global climate change. Ecosystems are enhanced by the presence of species with three-dimensional growth. The study of the growth, resilience, and recovery capability of those species provides valuable information on the conservation status of entire habitats. We discuss here a state-of-the art solution to speed up the monitoring of benthic population through the automatic or assisted analysis of underwater visual data.Source: ERCIM news 2020 (2020): 17–18.

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


2020 Journal article Restricted

LoopyCuts: Practical Feature-Preserving Block Decomposition for Strongly Hex-Dominant Meshing
Livesu M, Pietroni N., Puppo E., Sheffer A., Cignoni P.
We present a new fully automatic block-decomposition algorithm for feature preserving, strongly hex-dominant meshing, that yields results with a drastically larger percentage of hex elements than prior art. Our method is guided by a surface field that conforms to both surface curvature and feature lines, and exploits an ordered set of cutting loops that evenly cover the input surface, defining an arrangement of loops suitable for hex-element generation. We decompose the solid into coarse blocks by iteratively cutting it with surfaces bounded by these loops. The vast majority of the obtained blocks can be turned into hexahedral cells via simple midpoint subdivision. Our method produces pure hexahedral meshes in approximately 80% of the cases, and hex-dominant meshes with less than 2% non-hexahedral cells in the remaining cases. We demonstrate the robustness of our method on 70+ models, including CAD objects with features of various complexity, organic and synthetic shapes, and provide extensive comparisons to prior art, demonstrating its superiority.Source: ACM transactions on graphics 39 (2020): 1–17. doi:10.1145/3386569.3392472
DOI: 10.1145/3386569.3392472

See at: ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | dl.acm.org Restricted | ACM Transactions on Graphics Restricted | CNR ExploRA Restricted


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 Restricted

Turning a Smartphone Selfie into a Studio Portrait
Capece N., Banterle F., Cignoni P., Ganovelli F., Erra U., Potel M.
We introduce a novel algorithm that turns a flash selfie taken with a smartphone into a studio-like photograph with uniform lighting. Our method uses a convolutional neural network trained on a set of pairs of photographs acquired in a controlled environment. For each pair, we have one photograph of a subject's face taken with the camera flash enabled and another one of the same subject in the same pose illuminated using a photographic studio-lighting setup. We show how our method can amend lighting artifacts introduced by a close-up camera flash, such as specular highlights, shadows, and skin shine.Source: IEEE computer graphics and applications 40 (2020): 140–147. doi:10.1109/MCG.2019.2958274
DOI: 10.1109/mcg.2019.2958274

See at: IEEE Computer Graphics and Applications Restricted | IEEE Computer Graphics and Applications Restricted | ieeexplore.ieee.org Restricted | IEEE Computer Graphics and Applications Restricted | IEEE Computer Graphics and Applications Restricted | CNR ExploRA Restricted | IEEE Computer Graphics and Applications Restricted | IEEE Computer Graphics and Applications Restricted | IEEE Computer Graphics and Applications Restricted


2020 Journal article Open Access OPEN

A bending-active twisted-arch plywood structure: computational design and fabrication of the FlexMaps Pavilion
Laccone F., Malomo L., Pérez J., Pietroni N., Ponchio F., Bickel B., Cignoni P.
Bending-active structures are able to efficiently produce complex curved shapes from flat panels. The desired deformation of the panels derives from the proper selection of their elastic properties. Optimized panels, called FlexMaps, are designed such that, once they are bent and assembled, the resulting static equilibrium configuration matches a desired input 3D shape. The FlexMaps elastic properties are controlled by locally varying spiraling geometric mesostructures, which are optimized in size and shape to match specific bending requests, namely the global curvature of the target shape. The design pipeline starts from a quad mesh representing the input 3D shape, which defines the edge size and the total amount of spirals: every quad will embed one spiral. Then, an optimization algorithm tunes the geometry of the spirals by using a simplified pre-computed rod model. This rod model is derived from a non-linear regression algorithm which approximates the non-linear behavior of solid FEM spiral models subject to hundreds of load combinations. This innovative pipeline has been applied to the project of a lightweight plywood pavilion named FlexMaps Pavilion, which is a single-layer piecewise twisted arch that fits a bounding box of 3.90x3.96x3.25 meters. This case study serves to test the applicability of this methodology at the architectural scale. The structure is validated via FE analyses and the fabrication of the full scale prototype.Source: SN Applied Sciences 2 (2020). doi:10.1007/s42452-020-03305-w
DOI: 10.1007/s42452-020-03305-w
Project(s): EVOCATION via OpenAIRE

See at: link.springer.com Open Access | SN Applied Sciences Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | SN Applied Sciences Restricted | SN Applied Sciences Restricted | SN Applied Sciences Restricted | SN Applied Sciences Restricted


2020 Conference article Open Access OPEN

Automated Design and Analysis of Reinforced and Post-Tensioned Glass Shells
Laccone F., Malomo L., Pietroni N., Froli M., Cignoni P.
Shells made of structural glass are beautiful objects from both the aesthetics and the engineering point of view. However, they pose two significant challenges. The first one is to assure adequate safety and redundancy concerning possible global collapse. Being single-layered, in a shell made of structural glass, the brittle cracking of a single pane can lead to a sudden propagation of failure, up to instability. The second one is to guarantee cheap replacing possibilities for potentially collapsed components. This research explores a novel concept to address both requirements, where glass is both post-tensioned and reinforced and develops the research on TVT post-tensioned glass beams. Following the Fail-Safe Design (FSD) principles, a steel reinforcement relieves glass deficiencies (i.e. brittleness and low tensile strength). Following the Damage Avoidance Design (DAD) principles, glass segmentation and post-tensioning avoid the propagation of cracks. Up to now, glass-steel systems were limited to mono-dimensional elements (such as beams and columns) or simple bi-dimensional elements (arches, domes, barrel vaults). Instead, massive structures are usually realized as grid shells, where glass is used as simple cladding. This research investigates piecewise triangulated glass shells to enable the creation of 3D free-form glass-steel systems, where glass is load-bearing material. Hence, laminated glass panels are mechanically coupled with a filigree steel truss, whose elements are placed at the edges of the panel and act as an unbonded reinforcement. In a performance-based perspective, these steel trusses can be sized to bear at least the weight of all panels in the occurrence of simultaneous cracks (worst-case scenario). The panels are post-tensioned using a set of edge-aligned cables that add beneficial compressive stress on glass to prevent crack initiation. The cable placement and accompanying pre-loads are derived with an optimization strategy that minimizes the tensile stress acting on the shell. This optimization procedure also considers the practical constraints involved in the process. The results obtained through this automated procedure are later investigated using nonlinear FE analyses. The resulting structures optimize the total material usage providing contemporarily both transparency and load-bearing capabilities. Posttensioned shells excel in static performances, achieving high stiffness and good redundancy for the worst-case scenario, and improve the structural lightness and the visual impact with respect to state-of-the-art competitors.Source: Challenging Glass 7 Conference on Architectural and Structural Applications of Glass, Ghent University, September 2020

See at: journals.open.tudelft.nl Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


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


2020 Journal article Open Access OPEN

Real-World textured things: a repository of textured models generated with modern photo-reconstruction tools
Maggiordomo A., Ponchio F., Cignoni P., Tarini M.
We are witnessing a proliferation of textured 3D models captured from the real world with automatic photo-reconstruction tools by people and professionals without a proper technical background in computer graphics. Digital 3D models of this class come with a unique set of characteristics and defects - especially concerning their parametrization - setting them starkly apart from 3D models originating from other, more traditional, sources. We study this class of 3D models by collecting a significant number of representatives and quantitatively evaluating their quality according to several metrics. These include a new invariant metric we carefully design to assess the amount of fragmentation of the UV map, which is one of the main weaknesses potentially hindering the usability of these models. Our results back the widely shared notion that models of this new class are still not fit for direct use in downstream applications (such as videogames), and require challenging processing steps. Regrettably, existing automatic geometry processing tools are not always up to the task: for example, we verify that the available tools for UV optimization often fail due to mesh inconsistencies, geometric and topological noise, excessive resolution, or other factors; moreover, even when an output is produced, it rarely represents a significant improvement over the input (according to the aforementioned measures). Therefore, we argue that further advancements are required by the computer graphics and geometry processing communities specifically targeted at this class of models. Towards this goal, we share the models we collected in this study as a new public repository, Real-World Textured Things (RWTT), intended as a benchmark to systematic field-test and compare future algorithms. RWTT consists of 568 carefully selected textured 3D models representative of the most popular photo-reconstruction tools currently available. We also provide a web interface to browse the dataset by the metadata we collected during our experiments and a tool, TexMetro, to compute the same set of measures on generic UV mapped datasets.Source: Computer aided geometric design 83 (2020). doi:10.1016/j.cagd.2020.101943
DOI: 10.1016/j.cagd.2020.101943
Project(s): ENCORE via OpenAIRE

See at: arXiv.org e-Print Archive Open Access | Computer Aided Geometric Design Open Access | Archivio Istituzionale della Ricerca dell'Università degli Studi di Milano Open Access | Computer Aided Geometric Design Restricted | Computer Aided Geometric Design Restricted | Computer Aided Geometric Design Restricted | Computer Aided Geometric Design Restricted | Computer Aided Geometric Design Restricted | CNR ExploRA Restricted | Computer Aided Geometric Design Restricted | www.sciencedirect.com Restricted | Computer Aided Geometric Design Restricted


2020 Journal article Open Access OPEN

On improving the training of models for the semantic segmentation of benthic communities from orthographic imagery
Pavoni G., Corsini M., Callieri M., Fiameni G., Edwards C., Cignoni P.
The semantic segmentation of underwater imagery is an important step in the ecological analysis of coral habitats. To date, scientists produce fine-scale area annotations manually, an exceptionally time-consuming task that could be efficiently automatized by modern CNNs. This paper extends our previous work presented at the 3DUW'19 conference, outlining the workflow for the automated annotation of imagery from the first step of dataset preparation, to the last step of prediction reassembly. In particular, we propose an ecologically inspired strategy for an efficient dataset partition, an over-sampling methodology targeted on ortho-imagery, and a score fusion strategy. We also investigate the use of different loss functions in the optimization of a Deeplab V3+ model, to mitigate the class-imbalance problem and improve prediction accuracy on coral instance boundaries. The experimental results demonstrate the effectiveness of the ecologically inspired split in improving model performance, and quantify the advantages and limitations of the proposed over-sampling strategy. The extensive comparison of the loss functions gives numerous insights on the segmentation task; the Focal Tversky, typically used in the context of medical imaging (but not in remote sensing), results in the most convenient choice. By improving the accuracy of automated ortho image processing, the results presented here promise to meet the fundamental challenge of increasing the spatial and temporal scale of coral reef research, allowing researchers greater predictive ability to better manage coral reef resilience in the context of a changing environment.Source: Remote sensing (Basel) 12 (2020). doi:10.3390/RS12183106
DOI: 10.3390/rs12183106

See at: Remote Sensing Open Access | Remote Sensing Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | Remote Sensing Open Access | Remote Sensing Open Access


2020 Conference article Open Access OPEN

Another Brick in the Wall: Improving the Assisted Semantic Segmentation of Masonry Walls
Pavoni G., Giuliani F., De Falco A., Corsini M., Ponchio F., Callieri M., Cignoni P.
In Architectural Heritage, the masonry's interpretation is an essential instrument for analyzing the construction phases, the assessment of structural properties, and the monitoring of its state of conservation. This work is generally carried out by specialists that, based on visual observation and their knowledge, manually annotate ortho-images of the masonry generated by photogrammetric surveys. This results in vectorial thematic maps segmented according to their construction technique (isolating areas of homogeneous materials/structure/texture) or state of conservation, including degradation areas and damaged parts. This time-consuming manual work, often done with tools that have not been designed for this purpose, represents a bottleneck in the documentation and management workflow and is a severely limiting factor in monitoring large-scale monuments (e.g.city walls). This paper explores the potential of AI-based solutions to improve the efficiency of masonry annotation in Architectural Heritage. This experimentation aims at providing interactive tools that support and empower the current workflow, benefiting from specialists' expertise.Source: 18th Eurographics Workshop on Graphics and Cultural Heritage, pp. 43–51, Online event, 18-19/11/2020
DOI: 10.2312/gch.20201291

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2020 Journal article Restricted

Challenges in the deep learning-based semantic segmentation of benthic communities from Ortho-images
Pavoni G., Corsini M., Pedersen N., Petrovic V., Cignoni P.
Since the early days of the low-cost camera development, the collection of visual data has become a common practice in the underwater monitoring field. Nevertheless, video and image sequences are a trustworthy source of knowledge that remains partially untapped. Human-based image analysis is a time-consuming task that creates a bottleneck between data collection and extrapolation. Nowadays, the annotation of biologically meaningful information from imagery can be efficiently automated or accelerated by convolutional neural networks (CNN). Presenting our case studies, we offer an overview of the potentialities and difficulties of accurate automatic recognition and segmentation of benthic species. This paper focuses on the application of deep learning techniques to multi-view stereo reconstruction by-products (registered images, point clouds, ortho-projections), considering the proliferation of these techniques among the marine science community. Of particular importance is the need to semantically segment imagery in order to generate demographic data vital to understand and explore the changes happening within marine communities.Source: Applied geomatics (Print) (2020). doi:10.1007/s12518-020-00331-6
DOI: 10.1007/s12518-020-00331-6

See at: Applied Geomatics Restricted | Applied Geomatics Restricted | Applied Geomatics Restricted | Applied Geomatics Restricted | CNR ExploRA Restricted


2020 Journal article Restricted

DHFSlicer: Double Height-Field Slicing for Milling Fixed-Height Materials
Yang J., Araujo C., Vining N., Ferguson Z., Rosales E., Panozzo D., Lefevbre S., Cignoni P., Sheffer A.
3-axis milling enables cheap and precise fabrication of target objects from precut slabs of materials such as wood or stone. However, the space of directly millable shapes is limited since a 3-axis mill can only carve a height-field (HF) surface during each milling and their size is bounded by the slab dimensions, one of which, the height, is typically significantly smaller than the other two for many typical materials. Extending 3-axis milling of precut slabs to general arbitrarily-sized shapes requires decomposing them into bounded-height 3-axis millable parts, or slices, which can be individually milled and then assembled to form the target object. We present DHFSlicer, a novel decomposition method that satisfies the above constraints and significantly reduces both milling time and material waste compared to alternative approaches. We satisfy the fabrication constraints by partitioning target objects into double height-field (DHF) slices, which can be fabricated using two milling passes: the HF surface accessible from one side is milled first, the slice is then flipped using appropriate fixtures, and then the second, remaining, HF surface is milled. DHFSlicer uses an efficient coarse-to-fine decomposition process: It first partitions the inputs into maximally coarse blocks that satisfy a local DHF criterion with respect to per-block milling axes, and then cuts each block into well-sized DHF slices. It minimizes milling time and material waste by keeping the slice count small, and maximizing slice height. We validate our method by embedding it within an end-to-end DHF milling pipeline and fabricating objects from slabs of foam, wood, and MDF; demonstrate that using the obtained slices reduces milling time and material waste by 42% on average compared to existing automatic alternatives; and highlight the benefits of DHFSlicer via extensive ablation studies.Source: ACM transactions on graphics 39 (2020). doi:10.1145/3414685.3417810
DOI: 10.1145/3414685.3417810

See at: ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | dl.acm.org Restricted | ACM Transactions on Graphics Restricted | CNR ExploRA Restricted