Browsing by Author "Marton, Fabio"

Now showing 1 - 6 of 6
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    Ebb & Flow: Uncovering Costantino Nivola's Olivetti Sandcast through 3D Fabrication and Virtual Exploration
    (The Eurographics Association, 2022) Ahsan, Moonisa; Altea, Giuliana; Bettio, Fabio; Callieri, Marco; Camarda, Antonella; Cignoni, Paolo; Gobbetti, Enrico; Ledda, Paolo; Lutzu, Alessandro; Marton, Fabio; Mignemi, Giuseppe; Ponchio, Federico; Ponchio, Federico; Pintus, Ruggero
    We report on the outcomes of a large multi-disciplinary project targeting the physical reproduction and virtual documentation and exploration of the Olivetti sandcast, a monumental (over 100m2) semi-abstract frieze by the Italian sculptor Costantino Nivola. After summarizing the goal and motivation of the project, we provide details on the acquisition and processing steps that led to the creation of a 3D digital model. We then discuss the technical details and the challenges that we have faced for the physical fabrication process of a massive physical replica, which was the centerpiece of a recent exhibition. We finally discuss the design and application of an interactive web-based tool for the exploration of an annotated virtual replica. The main components of the tool will be released as open source.
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    Exploiting Neighboring Pixels Similarity for Effective SV-BRDF Reconstruction from Sparse MLICs
    (The Eurographics Association, 2021) Pintus, Ruggero; Ahsan, Moonisa; Marton, Fabio; Gobbetti, Enrico; Hulusic, Vedad and Chalmers, Alan
    We present a practical solution to create a relightable model from Multi-light Image Collections (MLICs) acquired using standard acquisition pipelines. The approach targets the difficult but very common situation in which the optical behavior of a flat, but visually and geometrically rich object, such as a painting or a bas relief, is measured using a fixed camera taking few images with a different local illumination. By exploiting information from neighboring pixels through a carefully crafted weighting and regularization scheme, we are able to efficiently infer subtle per-pixel analytical Bidirectional Reflectance Distribution Functions (BRDFs) representations from few per-pixel samples. The method is qualitatively and quantitatively evaluated on both synthetic data and real paintings in the scope of image-based relighting applications.
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    A Framework for GPU-accelerated Exploration of Massive Time-varying Rectilinear Scalar Volumes
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Marton, Fabio; Agus, Marco; Gobbetti, Enrico; Gleicher, Michael and Viola, Ivan and Leitte, Heike
    We introduce a novel flexible approach to spatiotemporal exploration of rectilinear scalar volumes. Our out-of-core representation, based on per-frame levels of hierarchically tiled non-redundant 3D grids, efficiently supports spatiotemporal random access and streaming to the GPU in compressed formats. A novel low-bitrate codec able to store into fixed-size pages a variable-rate approximation based on sparse coding with learned dictionaries is exploited to meet stringent bandwidth constraint during time-critical operations, while a near-lossless representation is employed to support high-quality static frame rendering. A flexible high-speed GPU decoder and raycasting framework mixes and matches GPU kernels performing parallel object-space and image-space operations for seamless support, on fat and thin clients, of different exploration use cases, including animation and temporal browsing, dynamic exploration of single frames, and high-quality snapshots generated from near-lossless data. The quality and performance of our approach are demonstrated on large data sets with thousands of multi-billion-voxel frames.
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    Guiding Lens-based Exploration using Annotation Graphs
    (The Eurographics Association, 2021) Ahsan, Moonisa; Marton, Fabio; Pintus, Ruggero; Gobbetti, Enrico; Frosini, Patrizio and Giorgi, Daniela and Melzi, Simone and Rodolà, Emanuele
    We introduce a novel approach for guiding users in the exploration of annotated 2D models using interactive visualization lenses. Information on the interesting areas of the model is encoded in an annotation graph generated at authoring time. Each graph node contains an annotation, in the form of a visual markup of the area of interest, as well as the optimal lens parameters that should be used to explore the annotated area and a scalar representing the annotation importance. Graph edges are used, instead, to represent preferred ordering relations in the presentation of annotations. A scalar associated to each edge determines the strength of this prescription. At run-time, the graph is exploited to assist users in their navigation by determining the next best annotation in the database and moving the lens towards it when the user releases interactive control. The selection is based on the current view and lens parameters, the graph content and structure, and the navigation history. This approach supports the seamless blending of an automatic tour of the data with interactive lens-based exploration. The approach is tested and discussed in the context of the exploration of multi-layer relightable models.
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    MTV-Player: Interactive Spatio-Temporal Exploration of Compressed Large-Scale Time-Varying Rectilinar Scalar Volumes
    (The Eurographics Association, 2019) Díaz, Jose; Marton, Fabio; Gobbetti, Enrico; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    We present an approach for supporting fully interactive exploration of massive time-varying rectilinear scalar volumes on commodity platforms. We decompose each frame into a forest of bricked octrees. Each brick is further subdivided into smaller blocks, which are compactly approximated by quantized variable-length sparse linear combinations of prototype blocks stored in a data-dependent dictionary learned from the input sequence. This variable bit-rate compact representation, obtained through a tolerance-driven learning and approximation process, is stored in a GPU-friendly format that supports direct adaptive streaming to the GPU with spatial and temporal random access. An adaptive compression-domain renderer closely coordinates off-line data selection, streaming, decompression, and rendering. The resulting system provides total control over the spatial and temporal dimensions of the data, supporting the same exploration metaphor as traditional video players. Since we employ a highly compressed representation, the bandwidth provided by current commodity platforms proves sufficient to fully stream and render dynamic representations without relying on partial updates, thus avoiding any unwanted dynamic effects introduced by current incremental loading approaches. Moreover, our variable-rate encoding based on sparse representations provides high-quality approximations, while offering real-time decoding and rendering performance. The quality and performance of our approach is demonstrated on massive time-varying datasets at the terascale, which are nonlinearly explored at interactive rates on a commodity graphics PC.
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    A Novel Approach for Exploring Annotated Data With Interactive Lenses
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Bettio, Fabio; Ahsan, Moonisa; Marton, Fabio; Gobbetti, Enrico; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana von
    We introduce a novel approach for assisting users in exploring 2D data representations with an interactive lens. Focus-andcontext exploration is supported by translating user actions to the joint adjustments in camera and lens parameters that ensure a good placement and sizing of the lens within the view. This general approach, implemented using standard device mappings, overcomes the limitations of current solutions, which force users to continuously switch from lens positioning and scaling to view panning and zooming. Navigation is further assisted by exploiting data annotations. In addition to traditional visual markups and information links, we associate to each annotation a lens configuration that highlights the region of interest. During interaction, an assisting controller determines the next best lens in the database based on the current view and lens parameters and the navigation history. Then, the controller interactively guides the user's lens towards the selected target and displays its annotation markup. As only one annotation markup is displayed at a time, clutter is reduced. Moreover, in addition to guidance, the navigation can also be automated to create a tour through the data. While our methods are generally applicable to general 2D visualization, we have implemented them for the exploration of stratigraphic relightable models. The capabilities of our approach are demonstrated in cultural heritage use cases. A user study has been performed in order to validate our approach.