Reconstruction of ancient greek painting in the context of modern digital technologies
DOI:
https://doi.org/10.18372/2415-8151.22.15396Keywords:
reconstruction, ancient greek painting, encaustics, cameo, drawing, composition, culture, artistic task, machine learningAbstract
Explore the possibility of forming an algorithm that allows for the reconstruction of the lost compositions of easel painting by outstanding masters of the Ancient Wurld.The purpose. Form an algorithm of the scheme of actions based onon the basis of the received historical information allowing to make the reconstruction of the lost compositions of easel painting of outstanding masters of Ancient Greece.Methodology. In the study, the following research methods were used:1) analytical method, by which the current literature had been analyzed;2) theoretical and conceptual method, which made it possible to determine the conditions necessary for the implementation of IT-technology into cultural and artistic practice; The study used the methods of computer modeling and analysis, which made it possible to increase the accuracy of the results. The authors of the article consistently consider the algorithm of actions necessary to restore the lost works of the past. The work takes into account the technological features of the layer-by-layer painting of the Ancient World and analyzes the color scheme used by the masters of antiquity. For clarity, the authors have created a special scheme — a color square. The creation of this material was preceded by a deep study of ancient sources, in particular the works of Pliny the Elder. Results. The main elements necessary for the restoration of the lost pictorial work of art have been established. The main reconstruction algorithm is stated: drawing, composition and methodology for creating a work of antique art. Hellenistic Greek colouristic is systematized according to the “Color square” scheme. All this information can be used in deep machine learning technologies according to certain algorithms and can give very interesting results.The scientificance novelty. Consist in the creation of a scheme of actions aimed at restoring the image as close as possible to the lost original on the basis of the preserved literary and material artifacts. Practical significance. This algorithm can be useful when creating computer software designed to recreate lost works of the past. Such a system will be needed in such fields as archeology and art history. The technique is ideal for use in deep machine learning technologies. To carry out the reconstruction of a specific work, the main aspects are considered: origin, development, principles of classical painting, technology, influence on other types of fine art (philosophy, utilitarian application, subject matter). The research methodology is based on the use of historical, cultural, art history and biographical approaches.References
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