Browsing by Author "Ahsan, Moonisa"

Now showing 1 - 3 of 3
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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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    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 RodolĂ , 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.