DSpace Repository :: Browsing by Author "Giachetti, Andrea"

Browsing by Author "Giachetti, Andrea"

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Aging Prediction of Cultural Heritage Samples Based on Surface Microgeometry
(The Eurographics Association, 2018) Ciortan, Irina Mihaela; Marchioro, Giacomo; Daffara, Claudia; Pintus, Ruggero; Gobbetti, Enrico; Giachetti, Andrea; Sablatnig, Robert and Wimmer, Michael
A critical and challenging aspect for the study of Cultural Heritage (CH) assets is related to the characterization of the materials that compose them and to the variation of these materials with time. In this paper, we exploit a realistic dataset of artificially aged metallic samples treated with different coatings commonly used for artworks' protection in order to evaluate different approaches to extract material features from high-resolution depth maps. In particular, we estimated, on microprofilometric surface acquisitions of the samples, performed at different aging steps, standard roughness descriptors used in materials science as well as classical and recent image texture descriptors. We analyzed the ability of the features to discriminate different aging steps and performed supervised classification tests showing the feasibility of a texture-based aging analysis and the effectiveness of coatings in reducing the surfaces' change with time.
Approximating Shapes with Standard and Custom 3D Printed LEGO Bricks
(The Eurographics Association, 2021) Fanni, Filippo Andrea; Dal Bello, Alberto; Sbardellini, Simone; Giachetti, Andrea; Frosini, Patrizio and Giorgi, Daniela and Melzi, Simone and Rodolà, Emanuele
In this paper, we present a work-in-progress aimed at developing a pipeline for the fabrication of shapes reproducing digital models with a combination of standard LEGO bricks and 3D printed custom elements. The pipeline starts searching for the ideal alignment of the 3D model with the brick grid. It then employs a novel approach for shape "legolization" using a outside-in heuristic to limit critical configuration, and separates an external shell and an internal part. Finally, it exploits shape booleans to create the external custom parts to be 3D printed.
A Comparison of Navigation Techniques in a Virtual Museum Scenario
(The Eurographics Association, 2019) Caputo,Ariel; Borin, Federico; Giachetti, Andrea; Rizvic, Selma and Rodriguez Echavarria, Karina
Thanks to the recent availability of low-cost immersive Virtual Reality (VR) devices, applications like Virtual Museums, where the users can explore fictional or recreated buildings hosting different artworks, are becoming increasingly popular. Different solutions can be implemented to enable users' navigation in an immersive Virtual Museum and the choice of the best one for a specific application is not easy, as several issues must be taken into account, like motion sickness, user's freedom, loss of orientation. In this work, we propose a novel locomotion technique called Map Overview Teleport, particularly suitable for exploration of virtual museums and compare it with standard ones in a specifically designed user study. The outcomes of the experiment give useful insights into the design of effective applications.
Crack Detection in Single- and Multi-Light Images of Painted Surfaces using Convolutional Neural Networks
(The Eurographics Association, 2019) Dulecha, Tinsae Gebrechristos; Giachetti, Andrea; Pintus, Ruggero; Ciortan, Irina; Villanueva, Alberto Jaspe; Gobbetti, Enrico; Rizvic, Selma and Rodriguez Echavarria, Karina
Cracks represent an imminent danger for painted surfaces that needs to be alerted before degenerating into more severe aging effects, such as color loss. Automatic detection of cracks from painted surfaces' images would be therefore extremely useful for art conservators; however, classical image processing solutions are not effective to detect them, distinguish them from other lines or surface characteristics. A possible solution to improve the quality of crack detection exploits Multi-Light Image Collections (MLIC), that are often acquired in the Cultural Heritage domain thanks to the diffusion of the Reflectance Transformation Imaging (RTI) technique, allowing a low cost and rich digitization of artworks' surfaces. In this paper, we propose a pipeline for the detection of crack on egg-tempera paintings from multi-light image acquisitions and that can be used as well on single images. The method is based on single or multi-light edge detection and on a custom Convolutional Neural Network able to classify image patches around edge points as crack or non-crack, trained on RTI data. The pipeline is able to classify regions with cracks with good accuracy when applied on MLIC. Used on single images, it can give still reasonable results. The analysis of the performances for different lighting directions also reveals optimal lighting directions.
Effective Interactive Visualization of Neural Relightable Images in a Web-based Multi-layered Framework
(The Eurographics Association, 2023) Righetto, Leonardo; Bettio, Fabio; Ponchio, Federico; Giachetti, Andrea; Gobbetti, Enrico; Bucciero, Alberto; Fanini, Bruno; Graf, Holger; Pescarin, Sofia; Rizvic, Selma
Relightable images created from Multi-Light Image Collections (MLICs) are one of the most commonly employed models for interactive object exploration in cultural heritage. In recent years, neural representations have been shown to produce higherquality images, at similar storage costs, with respect to the more classic analytical models such as Polynomial Texture Maps (PTM) or Hemispherical Harmonics (HSH). However, their integration in practical interactive tools has so far been limited due to the higher evaluation cost, making it difficult to employ them for interactive inspection of large images, and to the difficulty in integration cost, due to the need to incorporate deep-learning libraries in relightable renderers. In this paper, we illustrate how a state-of-the-art neural reflectance model can be directly evaluated, using common WebGL shader features, inside a multiplatform renderer. We then show how this solution can be embedded in a scalable framework capable to handle multi-layered relightable models in web settings. We finally show the performance and capabilities of the method on cultural heritage objects.
EUROGRAPHICS 2019: CGF 38-2 STARs Frontmatter
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Giachetti, Andrea; Rushmeyer, Holly; Giachetti, Andrea and Rushmeyer, Holly
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FloralSurf: Space-Filling Geodesic Ornaments
(The Eurographics Association, 2023) Albano, Valerio; Fanni, Filippo Andrea; Giachetti, Andrea; Pellacini, Fabio; Ritschel, Tobias; Weidlich, Andrea
We propose a method to generate floral patterns on manifolds without relying on parametrizations. Taking inspiration from the literature on procedural space-filling vegetation, these patterns are made of non-intersecting ornaments that are grown on the surface by repeatedly adding different types of decorative elements, until the whole surface is covered. Each decorative element is defined by a set of geodesic Bézier splines and a set of growth points from which to continue growing the ornaments. Ornaments are grown in a greedy fashion, one decorative element at a time. At each step, we analyze a set of candidates, and retain the one that maximizes surface coverage, while ensuring that it does not intersect other ornaments. All operations in our method are performed in the intrinsic metric of the surface, thus ensuring that the derived decorations have good coverage, with neither distortions nor discontinuities, and can be grown on complex surfaces. In our method, users control the decorations by selecting the size and shape of the decorative elements and the position of the growth points.We demonstrate decorations that vary in the length of the ornaments' lines, and the number, scale and orientation of the placed decorations. We show that these patterns mimic closely the design of hand-drawn objects. Our algorithm supports any manifold surface represented as triangle meshes. In particular, we demonstrate patterns generated on surfaces with high genus, with and without borders and holes, and that can include a mixture of thin and large features.
MLIC-Synthetizer: a Synthetic Multi-Light Image Collection Generator
(The Eurographics Association, 2019) Dulecha, Tinsae Gebrechristos; Dall'Alba, Andrea; Giachetti, Andrea; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
We present MLIC-Synthetizer, a Blender plugin specifically designed for the generation of a syntethic Multi-Light Image Collection using physically-based rendering. This tool makes easy to generate large amount of test data that can be useful for Photometric Stereo algorithms evaluation, validation of Reflectance Transformation Imaging calibration and processing method, relighting methods and more. Multi-pass rendering allows the generation of images with associated shadows and specularity ground truth maps, ground truth normals and material segmentation masks. Furthermore loops on material parameters allows the automatic generation of datasets with pre-defined material parameters ranges that can be used to train robust learning-based algorithms for 3D reconstruction, relight and material segmentation.
Objective and Subjective Evaluation of Virtual Relighting from Reflectance Transformation Imaging Data
(The Eurographics Association, 2018) Pintus, Ruggero; Dulecha, Tinsae; Jaspe, Alberto; Giachetti, Andrea; Ciortan, Irina; Gobbetti, Enrico; Sablatnig, Robert and Wimmer, Michael
Reflectance Transformation Imaging (RTI) is widely used to produce relightable models from multi-light image collections. These models are used for a variety of tasks in the Cultural Heritage field. In this work, we carry out an objective and subjective evaluation of RTI data visualization. We start from the acquisition of a series of objects with different geometry and appearance characteristics using a common dome-based configuration. We then transform the acquired data into relightable representations using different approaches: PTM, HSH, and RBF. We then perform an objective error estimation by comparing ground truth images with relighted ones in a leave-one-out framework using PSNR and SSIM error metrics. Moreover, we carry out a subjective investigation through perceptual experiments involving end users with a variety of backgrounds. Objective and subjective tests are shown to behave consistently, and significant differences are found between the various methods. While the proposed analysis has been performed on three common and state-of-the-art RTI visualization methods, our approach is general enough to be extended and applied in the future to new developed multi-light processing pipelines and rendering solutions, to assess their numerical precision and accuracy, and their perceptual visual quality.
Outside-in Priority-based Approximation of 3D Models in LEGO Bricks
(The Eurographics Association, 2022) Fanni, Filippo Andrea; Rossi, Elisa De; Giachetti, Andrea; Cabiddu, Daniela; Schneider, Teseo; Allegra, Dario; Catalano, Chiara Eva; Cherchi, Gianmarco; Scateni, Riccardo
In this paper, we discuss the problem of converting a 3D mesh into an assembly of LEGO blocks. The major challenge of this task is how to aggregate the voxels derived by the shape discretization into a set of standard bricks guaranteeing global connectivity. We propose an outside-in priority-based heuristic method based on the analysis of the critical regions that are more likely to cause the creation of a legal assembly to fail. We show that our graph-building heuristic provides relevant advantages, making it easier to obtain a connected graph with good properties with respect to the layer-based or random aggregation strategies applied in most of the optimization approaches. We also propose BRICKS, a novel dataset for the evaluation of aggregation strategies. It includes voxelizations at 3 different resolutions of 33 shapes and allows the easy comparison of different voxel aggregation strategies independently of the shape discretization step and also considering their scalability. We use it to evaluate our approach with respect to graph-based connectivity measures, showing the advantages of the proposed strategy.
Protein Shape Retrieval Contest
(The Eurographics Association, 2019) Langenfeld, Florent; Axenopoulos, Apostolos; Benhabiles, Halim; Daras, Petros; Giachetti, Andrea; Han, Xusi; Hammoudi, Karim; Kihara, Daisuke; Lai, Tuan M.; Liu, Haiguang; Melkemi, Mahmoud; Mylonas, Stelios K.; Terashi, Genki; Wang, Yufan; Windal, Feryal; Montes, Matthieu; Biasotti, Silvia and Lavoué, Guillaume and Veltkamp, Remco
This track aimed at retrieving protein evolutionary classification based on their surfaces meshes only. Given that proteins are dynamic, non-rigid objects and that evolution tends to conserve patterns related to their activity and function, this track offers a challenging issue using biologically relevant molecules. We evaluated the performance of 5 different algorithms and analyzed their ability, over a dataset of 5,298 objects, to retrieve various conformations of identical proteins and various conformations of ortholog proteins (proteins from different organisms and showing the same activity). All methods were able to retrieve a member of the same class as the query in at least 94% of the cases when considering the first match, but show more divergent when more matches were considered. Last, similarity metrics trained on databases dedicated to proteins improved the results.
Remote and Deviceless Manipulation of Virtual Objects in Mixed Reality
(The Eurographics Association, 2023) Caputo, Ariel; Bartolomioli, Riccardo; Giachetti, Andrea; Banterle, Francesco; Caggianese, Giuseppe; Capece, Nicola; Erra, Ugo; Lupinetti, Katia; Manfredi, Gilda
Deviceless manipulation of virtual objects in mixed reality (MR) environments is technically achievable with the current generation of Head-Mounted Displays (HMDs), as they track finger movements and allow you to use gestures to control the transformation. However, when the object manipulation is performed at some distance, and when the transform includes scaling, it is not obvious how to remap the hand motions over the degrees of freedom of the object. Different solutions have been implemented in software toolkits, but there are still usability issues and a lack of clear guidelines for the interaction design. We present a user study evaluating three solutions for the remote translation, rotation, and scaling of virtual objects in the real environment without using handheld devices. We analyze their usability on the practical task of docking virtual cubes on a tangible shelf from varying distances. The outcomes of our study show that the usability of the methods is strongly affected by the use of separate or integrated control of the degrees of freedom, by the use of the hands in a symmetric or specialized way, by the visual feedback, and by the previous experience of the users.
SHREC 2020 Track: River Gravel Characterization
(The Eurographics Association, 2020) Giachetti, Andrea; Biasotti, Silvia; Moscoso Thompson, Elia; Fraccarollo, Luigi; Nguyen, Quang; Nguyen, Hai-Dang; Tran, Minh-Triet; Arvanitis, Gerasimos; Romanelis, Ioannis; Fotis, Vlasis; Moustakas, Konstantinos; Tortorici, Claudio; Werghi, Naoufel; Berretti, Stefano; Schreck, Tobias and Theoharis, Theoharis and Pratikakis, Ioannis and Spagnuolo, Michela and Veltkamp, Remco C.
The quantitative analysis of the distribution of the different types of sands, gravels and cobbles shaping river beds is a very important task performed by hydrologists to derive useful information on fluvial dynamics and related processes (e.g., hydraulic resistance, sediment transport and erosion, habitat suitability. As the methods currently employed in the practice to perform this evaluation are expensive and time-consuming, the development of fast and accurate methods able to provide a reasonable estimate of the gravel distribution based on images or 3D scanning data would be extremely useful to support hydrologists in their work. To evaluate the suitability of state-of-the-art geometry processing tool to estimate the distribution from digital surface data, we created, therefore, a dataset including real captures of riverbed mockups, designed a retrieval task on it and proposed them as a challenge of the 3D Shape Retrieval Contest (SHREC) 2020. In this paper, we discuss the results obtained by the methods proposed by the groups participating in the contest and baseline methods provided by the organizers. Retrieval methods have been compared using the precision-recall curves, nearest neighbor, first tier, second tier, normalized discounted cumulated gain and average dynamic recall. Results show the feasibility of gravels characterization from captured surfaces and issues in the discrimination of mixture of gravels of different size.
Smart Tools and Applications in computer Graphics - Eurographics Italian Chapter Conference 2017: Frontmatter
(Eurographics Association, 2017) Giachetti, Andrea; Pingi, Paolo; Stanco, Filippo; Andrea Giachetti and Paolo Pingi and Filippo Stanco
State-of-the-art in Multi-Light Image Collections for Surface Visualization and Analysis
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Pintus, Ruggero; Dulecha, Tinsae Gebrechristos; Ciortan, Irina Mihaela; Gobbetti, Enrico; Giachetti, Andrea; Laramee, Robert S. and Oeltze, Steffen and Sedlmair, Michael
Multi-Light Image Collections (MLICs), i.e., stacks of photos of a scene acquired with a fixed viewpoint and a varying surface illumination, provide large amounts of visual and geometric information. In this survey, we provide an up-to-date integrative view of MLICs as a mean to gain insight on objects through the analysis and visualization of the acquired data. After a general overview of MLICs capturing and storage, we focus on the main approaches to produce representations usable for visualization and analysis. In this context, we first discuss methods for direct exploration of the raw data. We then summarize approaches that strive to emphasize shape and material details by fusing all acquisitions in a single enhanced image. Subsequently, we focus on approaches that produce relightable images through intermediate representations. This can be done both by fitting various analytic forms of the light transform function, or by locally estimating the parameters of physically plausible models of shape and reflectance and using them for visualization and analysis. We finally review techniques that improve object understanding by using illustrative approaches to enhance relightable models, or by extracting features and derived maps. We also review how these methods are applied in several, main application domains, and what are the available tools to perform MLIC visualization and analysis. We finally point out relevant research issues, analyze research trends, and offer guidelines for practical applications.
STRONGER: Simple TRajectory-based ONline GEsture Recognizer
(The Eurographics Association, 2021) Emporio, Marco; Caputo, Ariel; Giachetti, Andrea; Frosini, Patrizio and Giorgi, Daniela and Melzi, Simone and Rodolà, Emanuele
In this paper, we present STRONGER, a client-server solution for the online gesture recognition from captured hands' joints sequences. The system leverages a CNN-based recognizer improving current state-of-the-art solutions for segmented gestures classification, trained and tested for the online gesture recognition task on a recent benchmark including heterogeneous gestures. The recognizer provides good classification accuracy and a limited number of false positives on most of the gesture classes of the benchmark used and has been used to create a demo application in a Mixed Reality scenario using an Hololens 2 optical see through Head-Mounted Display with hand tracking capability.
SynthPS: a Benchmark for Evaluation of Photometric Stereo Algorithms for Cultural Heritage Applications
(The Eurographics Association, 2020) Dulecha, Tinsae Gebrechristos; Pintus, Ruggero; Gobbetti, Enrico; Giachetti, Andrea; Spagnuolo, Michela and Melero, Francisco Javier
Photometric Stereo (PS) is a technique for estimating surface normals from a collection of images captured from a fixed viewpoint and with variable lighting. Over the years, several methods have been proposed for the task, trying to cope with different materials, lights, and camera calibration issues. An accurate evaluation and selection of the best PS methods for different materials and acquisition setups is a fundamental step for the accurate quantitative reconstruction of objects' shapes. In particular, it would boost quantitative reconstruction in the Cultural Heritage domain, where a large amount of Multi-Light Image Collections are captured with light domes or handheld Reflectance Transformation Imaging protocols. However, the lack of benchmarks specifically designed for this goal makes it difficult to compare the available methods and choose the most suitable technique for practical applications. An ideal benchmark should enable the evaluation of the quality of the reconstructed normals on the kind of surfaces typically captured in real-world applications, possibly evaluating performance variability as a function of material properties, light distribution, and image quality. The evaluation should not depend on light and camera calibration issues. In this paper, we propose a benchmark of this kind, SynthPS, which includes synthetic, physically-based renderings of Cultural Heritage object models with different assigned materials. SynthPS allowed us to evaluate the performance of classical, robust and learning-based Photometric Stereo approaches on different materials with different light distributions, also analyzing their robustness against errors typically arising in practical acquisition settings, including robustness against gamma correction and light calibration errors.
Web-based Multi-layered Exploration of Annotated Image-based Shape and Material Models
(The Eurographics Association, 2019) Villanueva, Alberto Jaspe; Pintus, Ruggero; Giachetti, Andrea; Gobbetti, Enrico; Rizvic, Selma and Rodriguez Echavarria, Karina
We introduce a novel versatile approach for letting users explore detailed image-based shape and material models integrated with structured, spatially-associated descriptive information. We represent the objects of interest as a series of registered layers of image-based shape and material information. These layers are represented at multiple scales, and can come out of a variety of pipelines and include both RTI representations and spatially-varying normal and BRDF fields, eventually as a result of fusing multi-spectral data. An overlay image pyramid associates visual annotations to the various scales. The overlay pyramid of each layer can be easily authored at data preparation time using widely available image editing tools. At run-time, an annotated multi-layered dataset is made available to clients by a standard web server. Users can explore these datasets on a variety of devices, from mobile phones to large scale displays in museum installations, using JavaScript/WebGL2 clients capable to perform layer selection, interactive relighting and enhanced visualization, annotation display, and focus-and-context multiple-layer exploration using a lens metaphor. The capabilities of our approach are demonstrated on a variety of cultural heritage use cases involving different kinds of annotated surface and material models.

Browsing by Author "Giachetti, Andrea"

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