Preserving Sculptural Heritage in the Era of Digital Transformation: Methods and Challenges of 3D Art Assessment

Abstract

Sustainable digital cultural heritage is now an essential aspect of our lives. The rapid development of 3D technology in the historic preservation industry provides the means of documenting, recovering, and presenting cultural heritage items. However, the digital transformation of 3D sculpture heritage is often led by technology without effective evaluation indicators as a guide. This study compares effective assessment methods for digital forms with traditional art. Our approach uses semantic differential scales and machine learning regression models to assess the importance of fifteen artistic attributes. The semantic differential scale is improved based on 15 artistic attributes and proves to be effective in evaluating the value of digital artwork. This research finds that digital artwork is significantly more popular among young people compared with elderly people, especially for attributes like colour variation, saturation, and texture. The research also finds that complexity and social attributes are more important in predicting the value of the digital 3D model. Digital transformation is a viable method for preserving the artistic value of sculpture and improving cultural sustainability.