Eurographics Workshops and Symposia

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Browsing Eurographics Workshops and Symposia by Author "Ahsan, Moonisa"

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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.