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How to Analyze, Preserve, and Communicate Leonardo's Drawing? A Solution to Visualize in RTR Fine Art Graphics Established from “the Best Sense”

Published: 01 July 2021 Publication History

Abstract

Original hand drawings by Leonardo are astonishing collections of knowledge, superb representations of the artist's way of working, which proves the technical and cultural peak of the Renaissance era. However, due to their delicate and fragile nature, they are hard to manipulate and compulsory to preserve. To overcome this problem we developed, in a 10-year-long research program, a complete workflow to produce a system able to replace, investigate, describe and communicate ancient fine drawings through what Leonardo calls “the best sense” (i.e., the view), the so-called ISLe (InSightLeonardo). The outcoming visualization app is targeted to a wide audience made of museum visitors and, most importantly, art historians, scholars, conservators, and restorers. This article describes a specific feature of the workflow: the appearance modeling with the aim of an accurate Real-Time Rendering (RTR) visualization. This development is based on the direct observation of five among the most known Leonardo da Vinci's drawings, spanning his entire activity as a draftsman, and it is the result of an accurate analysis of drawing materials used by Leonardo, in which peculiarities of materials are digitally reproduced at the various scales exploiting solutions that favor the accuracy of perceived reproduction instead of the fidelity to the physical model and their ability to be efficiently implemented over a standard GPU-accelerated RTR pipeline. Results of the development are exemplified on five of Leonardo's drawings and multiple evaluations of the results, subjective and objective, are illustrated, aiming to assess potential and critical issues of the application.

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        cover image Journal on Computing and Cultural Heritage
        Journal on Computing and Cultural Heritage   Volume 14, Issue 3
        July 2021
        315 pages
        ISSN:1556-4673
        EISSN:1556-4711
        DOI:10.1145/3473560
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        Publication History

        Published: 01 July 2021
        Accepted: 01 November 2020
        Revised: 01 October 2020
        Received: 01 April 2020
        Published in JOCCH Volume 14, Issue 3

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        1. 3D digital artifact capture
        2. Color reproduction
        3. Leonardo da Vinci
        4. Material classification
        5. Real-Time Rendering
        6. Renaissance drawings
        7. Shaders
        8. analytic tools for scholars
        9. and reproduction

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