ABSTRACT:The digital management of architectural heritage information is still a complex problem, as a heritage object requires an integrated representation of various types of information in order to develop appropriate restoration or conservation strategies. Currently, there is extensive research focused on automatic procedures of segmentation and classification of 3D point clouds or meshes, which can accelerate the study of a monument and integrate it with heterogeneous information and attributes, useful to characterize and describe the surveyed object. The aim of this study is to propose an optimal, repeatable and reliable procedure to manage various types of 3D surveying data and associate them with heterogeneous information and attributes to characterize and describe the surveyed object. In particular, this paper presents an approach for classifying 3D heritage models, starting from the segmentation of their textures based on supervised machine learning methods. Experimental results run on three different case studies demonstrate that the proposed approach is effective and with many further potentials.

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Archaeological collections are crucial in heritage studies and are used every day for training archaeologists and cultural heritage specialists. The recent developments in 3D acquisition and visualization technology has contributed to the rapid emergence of a large number of 3D collections, whose production is often justified as the democratization of data and knowledge production. Despite the fact that several 3D datasets are now available online, it is not always clear how the data – once stored – may be engaged by archaeology students, and the possible challenges the students may face in the learning process. The goal of the Dynamic Collections project at Lund University is to develop a novel 3D web infrastructure designed to support higher education and research in archaeology. At the onset of the COVID-19 pandemic in the spring of 2020, all teaching at Lund University moved online, reinforcing the urgency for such an infrastructure. By letting a group of students test an early version of the system as part of their online teaching, we were able to study how they used and interacted with an archaeological collection in 3D and explore the intersection of digital methods and pedagogy in archaeology. This article presents the preliminary results from this experiment.