ABSTRACT:The evolution of Structure from Motion (SfM) techniques and their integration with the established procedures of classic stereoscopic photogrammetric survey have provided a very effective tool for the production of three-dimensional textured models. Such models are not only aesthetically pleasing but can also contain metric information, the quality of which depends on both survey type and applied processing methodologies. An open research topic in this area refers to checking attainable accuracy levels. The knowledge of such accuracy is essential, especially in the integration of models obtained through SfM with other models derived from different sensors or methods (laser scanning, classic photogrammetry ...). Accuracy checks may be conducted by either comparing SfM models against a reference one or measuring the deviation of control points identified on models and measured with classic topographic instrumentation and methodologies. This paper presents an analysis of attainable accuracy levels, according to different approaches of survey and data processing. For this purpose, a survey of the Church of San Miniato in Marcianella (Pisa, Italy), has been used. The dataset is an integration of laser scanning with terrestrial and UAV-borne photogrammetric surveys; in addition, a high precision topographic network was established for the specific purpose. In particular, laser scanning has been used for the interior and the exterior of the church, with the exclusion of the roof, while UAVs have been used for the photogrammetric survey of both roof, with horizontal strips, and façade, with vertical strips.

This work presents a semi-automatic approach to the 3D reconstruction of Heritage-Building Information Models from point clouds based on machine learning techniques. The use of digital information systems leveraging on three-dimensional (3D) representations in architectural heritage documentation and analysis is ever increasing. For the creation of such repositories, reality-based surveying techniques, such as photogrammetry and laser scanning, allow the fast collection of reliable digital replicas of the study objects in the form of point clouds. Besides, their output is raw and unstructured, and the transition to intelligible and semantic 3D representations is still a scarcely automated and time-consuming process requiring considerable human intervention. More refined methods for 3D data interpretation of heritage point clouds are therefore sought after. In tackling these issues, the proposed approach relies on (i) the application of machine learning techniques to semantically label 3D heritage data by identification of relevant geometric, radiometric and intensity features, and (ii) the use of the annotated data to streamline the construction of Heritage-Building Information Modeling (H-BIM) systems, where purely geometric information derived from surveying is associated with semantic descriptors on heritage documentation and management. The “Grand-Ducal Cloister” dataset, related to the emblematic case study of the Pisa Charterhouse, is discussed.

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Abstract. Research in the field of Cultural Heritage is increasingly moving towards the creation of digital information systems, in which the geometric representation of an artifact is linked to some external information, through meaningful tags. The process of attributing additional and structured information to various elements in a given digital model is customarily identified with the term semantic annotation; the added contextual information is associated, for instance, to analysis and conservation terms. Starting from the existing literature, aim of this work is to discuss how semantic annotations are used, in digital architectural heritage models, to link the geometrical representation of an artefact with knowledge-related information. Most consolidated methods -such as traditional mapping on 2D media, are compared with more recent approaches making the most of 3D representation. Reference is made, in particular, to Heritage-BIM techniques and to collaborative reality-based platforms, such as Aïoli (http://aioli.cloud). Potentialities and limits of the different solutions proposed in literature are critically discussed, also addressing future research challenges in Cultural Heritage application fields.

<p><strong>Abstract.</strong> Cultural heritage includes several cases of missing architectural element or entire buildings, due to destruction, replacement or radical changes caused over time by other structures. The investigation of these lost elements aimed at their virtual reconstruction, for both scientific and cultural-leisure applications, is therefore a topic of great interest. To this purpose, methodologies for surveying and photogrammetric processing provide a very powerful tool, extracting descriptive and geometric information, both 2-and 3-D, using diverse archive images. This paper presents the issues related to the use of archive images in photogrammetry, pointing out the need for an integrated approach to operations of virtual reconstruction of lost volumes. This approach provides a multidisciplinary effort, in order to evaluate all iconographic sources, of which images processed by geomatics techniques are a component. The paper also presents the early results of a reconstruction project of the <i>Palazzo di Cosimo de’ Medici</i>, in the <i>Fortezza Vecchia</i> site (Livorno, Italy), heavily damaged by World War II bombings and subsequently razed.</p>