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

• Published in: Journal on computing and cultural heritage 2021-07, Vol.14 (3), p.1-30
• Main Authors: Apollonio, Fabrizio Ivan, Foschi, Riccardo, Gaiani, Marco, Garagnani, Simone
• Format: Article
• Language: English
• ISSN: 1556-4673; 1556-4711
• DOI: 10.1145/3433606

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.