ACM Journal on Computing and Cultural Heritage最新文献

Digital architectural heritage content creation for virtual worlds nowadays is one of the most important challenges with the ever-increasing expenses of manual content development. Procedural modeling approaches have become a key tool for automating the design and reconstruction of structures and urban environments to disseminate them through appropriate multimedia approaches. This study presents a general architectural modeling system that combines the full generative power of shape grammars with the ease of use and flexibility of procedural modeling parameters which allows for the creation of heritage buildings that adhere to shape grammars. To evaluate the system, we conducted an initial user study with 20 participants from the Al-Zaytoonah university of Jordan to assess the user experience, user impression, and effectiveness of the system. Participants’ feedbacks were encouraging, indicating that the proposed approach could be effective and beneficial in assisting the creation of digital architectural heritage urban virtual content.

Linked Data is used in various fields as a new way of structuring and connecting data. Cultural heritage institutions have been using linked data to improve archival descriptions and facilitate the discovery of information. Most archival records have digital representations of physical artifacts in the form of scanned images that are non-machine-readable. Optical Character Recognition (OCR) recognizes text in images and translates it into machine-encoded text. This paper evaluates the impact of image processing methods and parameter tuning in OCR applied to typewritten cultural heritage documents. The approach uses a multi-objective problem formulation to minimize Levenshtein edit distance and maximize the number of words correctly identified with a non-dominated sorting genetic algorithm (NSGA-II) to tune the methods’ parameters. Evaluation results show that parameterization by digital representation typology benefits the performance of image pre-processing algorithms in OCR. Furthermore, our findings suggest that employing image pre-processing algorithms in OCR might be more suitable for typologies where the text recognition task without pre-processing does not produce good results. In particular, Adaptive Thresholding, Bilateral Filter, and Opening are the best-performing algorithms for the theatre plays’ covers, letters, and overall dataset, respectively, and should be applied before OCR to improve its performance.

The fact that the physical shapes of man-made objects are subject to overlapping influences—such as technological, economic, geographic, and stylistic progressions—holds great information potential. On the other hand, it is also a major analytical challenge to uncover these overlapping trends and to disentagle them in an unbiased way. This paper explores a novel mathematical approach to extract archaeological insights from ensembles of similar artifact shapes. We show that by considering all shape information in a find collection, it is possible to identify shape patterns that would be difficult to discern by considering the artifacts individually or by classifying shapes into predefined archaeological types and analyzing the associated distinguishing characteristics.

Recently, series of high-resolution digital representations of artifacts have become available. Such data sets enable the application of extremely sensitive and flexible methods of shape analysis. We explore this potential on a set of 3D models of ancient Greek and Roman sundials, with the aim of providing alternatives to the traditional archaeological method of “trend extraction by ordination” (typology). In the proposed approach, each 3D shape is represented as a point in a shape space—a high-dimensional, curved, non-Euclidean space. Proper consideration of its mathematical properties reduces bias in data analysis and thus improves analytical power. By performing regression in shape space, we find that for Roman sundials, the bend of the shadow-receiving surface of the sundials changes with the latitude of the location. This suggests that, apart from the inscribed hour lines, also a sundial’s shape was adjusted to the place of installation. As an example of more advanced inference, we use the identified trend to infer the latitude at which a sundial, whose location of installation is unknown, was placed.

We also derive a novel method for differentiated morphological trend assertion, building upon and extending the theory of geometric statistics and shape analysis. Specifically, we present a regression-based method for statistical normalization of shapes that serves as a means of disentangling parameter-dependent effects (trends) and unexplained variability. In addition, we show that this approach is robust to noise in the digital reconstructions of the artifact shapes.

Bilaterally symmetrical objects represent a large and important proportion of archaeological artifacts and biological objects. The identification of the plane of symmetry plays a vital role in quantifying surface asymmetry and producing profile drawings in archaeology and anthropology. The correct recognition of symmetry provides evidence to allow experts to restore damaged artifacts, assess consistency in artifact manufacture, and examine morphological variability in human development. With the increasing availability of archaeological and anthropological three-dimensional (3D) meshes, landmark-based and landmark-free morphometric methods for detecting planes of symmetry have both been proposed. However, the landmark-based approach requires manual identification of landmark locations, and hence they are time-consuming and prone to error. Additionally, the landmark-independent morphometric method is influenced by missing data. This study presents an effective landmark-free approach to approximate the best-fitted plane of symmetry from nearly bilaterally symmetrical objects by means of finding the plane with the minimum geometric differences between the original and mirrored meshes. Subsequently, a global and regional method is carried out to quantify surface asymmetry, reducing the effect of the size and orientation of 3D meshes on gross asymmetry detection. Finally, profile drawings are produced by computing the intersections of the plane of symmetry and 3D meshes. Both synthetic and real objects are used to evaluate the effectiveness and robustness of the proposed method. Our results show the approximated plane of symmetry generated by the proposed method is consistent with that determined by anatomical landmarks, and no significant differences in asymmetry ratio representing the degree of gross asymmetry are found between the landmark-based and proposed methods. These results demonstrate that the proposed method provides a suitable plane of symmetry from a bilaterally symmetrical object with small geometric distortion or simple missing geometry, thereby speeding up asymmetry detection and profile drawings.

Easily accessible characterization techniques such as X-ray fluorescence (XRF), Fourier Transform Infrared Spectroscopy (FTIR), or Raman spectroscopy, are at this moment the most commonly used analytical tools in heritage and conservation science. Materials identification in works of art is a fundamental step for understanding an object's history or an artist's technique. Comprehensive characterization and diagnosis of the various constituent materials in artworks can provide valuable information on the artist's working methods, as well as significant evidence for dating, provenance attribution, or forgery detection. The development of databases with high-quality data on the pure substances used as artists’ materials is of utmost importance for the identification and characterization of unknown samples. However, there are relatively few open access spectra libraries dedicated exclusively to the cultural heritage field. To address this need, within the frame of the postdoctoral project INFRA-ART, an open access spectral library of art-related materials has been developed. The database is an ongoing compilation of spectra that contains at this moment over 1,000 high-quality attenuated total reflection–FTIR, Raman, and XRF spectra associated with over 500 known reference materials. In this article, a summary of the database structure and design, functionality, and use is presented, in view of the dissemination of this new open access spectral library to the scientific community.

The surge of Mobile Virtual Reality (VR) applications is getting growing attention among researchers and practitioners. The recent literature demonstrates its benefits when used for education purposes, since virtual immersion yields promising results for learning. Leveraging this trend, within the so called “digital didactics”, the need to gauge VR’s effectiveness in the didactic field has become paramount; so far, a method to connect traditional evaluation strategies to novel VR-based learning is still broadly missing. This paper investigates the problem of quantifying the learning outcomes and proposes a new didactic evaluation method for the Digital Cultural Heritage (DCH) learning. This research, conducted in a higher education institute, proposes three new Key Performance Indicators, referring to Revised Bloom’s Taxonomy (RBT): Mnemonic (M), Transversal (T), and Disciplinary (D). A questionnaire was administered by the same teacher who holds the course, to evaluate how well the application communicated information. The participants have been subdivided into two groups with the same knowledge base. The first group (1ACAT) that represents the “VR group” used the app at home to deepen their subject studies; while the second group (1AGR) that represents the “control group” consulted and studied the app only before the test. The results have demonstrated that the “control group” has a greater ability to support purely mnemonic topics (1ACAT 46.9%, 1AGR 53.1%), such as dates and simple definitions. The skills reached by the “VR group” attest to both transveral (1ACAT 52.9%, 1AGR 47.1%) and disciplinary (1ACAT 52.5%, 1AGR 47.5%) knowledge. These results validate the use of VR in teaching, demonstrating both experiential value and student involvement, but even confirming the compensatory function of VR if compared with the irreplaceable role of teachers in guiding learners to learn.

Virtual Reality (VR) promises many benefits for the tourism industry. However, a review of tourism-related VR research shows that the roles of system quality and user personality remain largely unexplored. This study examines the causal relation underlying VR quality (information quality, interactivity, and visual attractiveness) and the user's personality (openness to experience, conscientiousness, and social influence) in conjunction with usability, attitude, and behavioural intention. We collected user data from a VR tourism experience of the Sangiran museum at Surakarta, Indonesia using a Head Mounted Device VR. The Sangiran museum is an archaeological excavation site recognised as a world heritage site by UNESCO. Two hundred eighteen valid responses were analysed using Structural Equation Modelling. The result suggests that only visual attractiveness positively impacts usability from a VR quality perspective, while openness to experience and social influence show significant positive evidence of attitude. These findings are discussed based on the practical and theoretical implications, including future research opportunities into VR tourism.