3D scanning of cultural heritage with consumer depth cameras

Three dimensional reconstruction of cultural heritage objects is an expensive and time-consuming process. Recent consumer real-time depth acquisition devices, like Microsoft Kinect, allow very fast and simple acquisition of 3D views. However 3D scanning with such devices is a challenging task due to the limited accuracy and reliability of the acquired data. This paper introduces a 3D reconstruction pipeline suited to use consumer depth cameras as hand-held scanners for cultural heritage objects. Several new contributions have been made to achieve this result. They include an ad-hoc filtering scheme that exploits the model of the error on the acquired data and a novel algorithm for the extraction of salient points exploiting both depth and color data. Then the salient points are used within a modified version of the ICP algorithm that exploits both geometry and color distances to precisely align the views even when geometry information is not sufficient to constrain the registration. The proposed method, although applicable to generic scenes, has been tuned to the acquisition of sculptures and in this connection its performance is rather interesting as the experimental results indicate

Fine Art Pattern Extraction and Recognition

This is a reprint of articles from the Special Issue published online in the open access journal Journal of Imaging (ISSN 2313-433X) (available at: https://www.mdpi.com/journal/jimaging/special issues/faper2020)

A Novel Framework for Highlight Reflectance Transformation Imaging

We propose a novel pipeline and related software tools for processing the multi-light image collections (MLICs) acquired in different application contexts to obtain shape and appearance information of captured surfaces, as well as to derive compact relightable representations of them. Our pipeline extends the popular Highlight Reflectance Transformation Imaging (H-RTI) framework, which is widely used in the Cultural Heritage domain. We support, in particular, perspective camera modeling, per-pixel interpolated light direction estimation, as well as light normalization correcting vignetting and uneven non-directional illumination. Furthermore, we propose two novel easy-to-use software tools to simplify all processing steps. The tools, in addition to support easy processing and encoding of pixel data, implement a variety of visualizations, as well as multiple reflectance-model-fitting options. Experimental tests on synthetic and real-world MLICs demonstrate the usefulness of the novel algorithmic framework and the potential benefits of the proposed tools for end-user applications.Terms: "European Union (EU)" & "Horizon 2020" / Action: H2020-EU.3.6.3. - Reflective societies - cultural heritage and European identity / Acronym: Scan4Reco / Grant number: 665091DSURF project (PRIN 2015) funded by the Italian Ministry of University and ResearchSardinian Regional Authorities under projects VIGEC and Vis&VideoLa

3D INTERPRETATION AND FUSION OF MULTIDISCIPLINARY DATA FOR HERITAGE SCIENCE: A REVIEW

Activities related to the protection of tangible heritage require extensive multidisciplinary documentation. The various raw data that occur have been oftentimes been processed, visualized and evaluated separately leading to aggregations of unassociated information of varying data types. In the direction of adopting complete approaches towards more effective decision making, the interpretation and fusion of these data in three dimensions, inserting topological information is deemed necessary. The present study addresses the achieved level of three-dimensional interpretation and fusion with geometric models of data originating from different fields, by providing an extensive review of the relevant literature. Additionally, it briefly discusses perspectives on techniques that could potentially be integrated with point clouds or models

Developing an interoperable cloud-based visualization workflow for 3D archaeological heritage data. The Palenque 3D Archaeological Atlas

In archaeology, 3D data has become ubiquitous, as researchers routinely capture high resolution photogrammetry and LiDAR models and engage in laborious 3D analysis and reconstruction projects at every scale: artifacts, buildings, and entire sites. The raw data and processed 3D models are rarely shared as their computational dependencies leave them unusable by other scholars. In this paper we outline a novel approach for cloud-based collaboration, visualization, analysis, contextualization, and archiving of multi-modal giga-resolution archaeological heritage 3D data. The Palenque 3D Archaeological Atlas builds on an open source WebGL systems that efficiently interlink, merge, present, and contextualize the Big Data collected at the ancient Maya city of Palenque, Mexico, allowing researchers and stakeholders to visualize, access, share, measure, compare, annotate, and repurpose massive complex archaeological datasets from their web-browsers