Hybridization of Convergent Photogrammetry, Computer Vision, and Artificial Intelligence for Digital Documentation of Cultural Heritage - A Case Study: The Magdalena Palace

2014 ◽  
Author(s):  
Oscar Cosido ◽  
Andres Iglesias ◽  
Akemi Galvez ◽  
Raffaele Catuogno ◽  
Massimiliano Campi ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Cultural Heritage ◽  
Digital Documentation

The Intersections of Creativity, Technology, and the Mind

2020 ◽  
pp. 123-140
Author(s):  
Audri Phillips
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Motion Capture ◽  
Human Mind ◽  
Media Technology ◽  
The Senses ◽  
Creativity Studies ◽  
The Mind ◽  
Immersive Technologies

This chapter examines the relationships between technology, the human mind, and creativity. The chapter cannot possibly cover the whole spectrum of the aforementioned; nonetheless, it covers highlights that especially apply to new immersive technologies. The nature of creativity, creativity studies, the tools, languages, and technology used to promote creativity are discussed. The part that the mind and the senses—particularly vision—play in immersive media technology, as well as robotics, artificial intelligence (AI), computer vision, and motion capture are also discussed. The immersive transmedia project Robot Prayers is offered as a case study of the application of creativity and technology working hand in hand.

scholarly journals HBIM IN A SEMANTIC 3D GIS DATABASE

2019 ◽  
Vol XLII-2/W11 ◽  
pp. 857-865 ◽  
Author(s):  
F. Matrone ◽  
E. Colucci ◽  
V. De Ruvo ◽  
A. Lingua ◽  
A. Spanò
Keyword(s):  
Cultural Heritage ◽  
3D Model ◽  
Recent Past ◽  
Architectural Heritage ◽  
Risk Zone ◽  
Architectural Elements ◽  
Digital Documentation ◽  
Santa Maria ◽  
The Church

<p><strong>Abstract.</strong> This work describes the different attempts and the consequent results derived from the integration of an HBIM model into an already structured spatial database (DB) and its 3D visualisation in a GIS project.</p><p>This study is connected to the European ResCult (Increasing Resilience of Cultural Heritage) project where a DB for multiscale analyses was defined. To test the methodology proposed, the case study of Santa Maria dei Miracoli church in Venice was chosen since it represents a complex architectural heritage piece in a risk zone, it has been subject to a vast restoration intervention in the recent past but a digital documentation and model concerning it was missing.</p><p>The 3D model of the church was structured in Revit as a HBIM, with the association of different kind of information and data related to the architectural elements by means of ‘shared parameters’ and ‘system families’. This procedure allows to reach an even higher Level of Detail (LOD4), but lead to some issues related to the semantic and software interoperability. To solve these problems the existing DB for the resilience of cultural heritage was extended adding a new entity representing the architectural elements designed in the BIM project.</p><p>The aim of the test is to understand how the data and attributes inserted in the HBIM are converted and handled when dealing with a GIS DB, stepping from the IFC to the CityGML standard, through the FME software.</p>

scholarly journals Development of an Optimised Dataset for Training a Deep Neural Network

2021 ◽  
Author(s):  
Callum Newman ◽  
Jon Petzing ◽  
Yee Mey Goh ◽  
Laura Justham
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Neural Networks ◽  
Computer Vision ◽  
Light Intensity ◽  
Test Performance ◽  
Deep Neural Network ◽  
Training Dataset ◽  
Multiple Factors

Artificial intelligence in computer vision has focused on improving test performance using techniques and architectures related to deep neural networks. However, improvements can also be achieved by carefully selecting the training dataset images. Environmental factors, such as light intensity, affect the image’s appearance and by choosing optimal factor levels the neural network’s performance can improve. However, little research into processes which help identify optimal levels is available. This research presents a case study which uses a process for developing an optimised dataset for training an object detection neural network. Images are gathered under controlled conditions using multiple factors to construct various training datasets. Each dataset is used to train the same neural network and the test performance compared to identify the optimal factors. The opportunity to use synthetic images is introduced, which has many advantages including creating images when real-world images are unavailable, and more easily controlled factors.

scholarly journals A Methodology for Semantic Enrichment of Cultural Heritage Images Using Artificial Intelligence Technologies

2021 ◽  
Vol 7 (8) ◽  
pp. 121
Author(s):  
Yalemisew Abgaz ◽  
Renato Rocha Souza ◽  
Japesh Methuku ◽  
Gerda Koch ◽  
Amelie Dorn
Keyword(s):  
Artificial Intelligence ◽  
Cultural Heritage ◽  
Cultural Values ◽  
New Technologies ◽  
Lessons Learned ◽  
Future Research ◽  
Semantic Web Technologies ◽  
Research Areas ◽  
Abstract Content

Cultural heritage images are among the primary media for communicating and preserving the cultural values of a society. The images represent concrete and abstract content and symbolise the social, economic, political, and cultural values of the society. However, an enormous amount of such values embedded in the images is left unexploited partly due to the absence of methodological and technical solutions to capture, represent, and exploit the latent information. With the emergence of new technologies and availability of cultural heritage images in digital formats, the methodology followed to semantically enrich and utilise such resources become a vital factor in supporting users need. This paper presents a methodology proposed to unearth the cultural information communicated via cultural digital images by applying Artificial Intelligence (AI) technologies (such as Computer Vision (CV) and semantic web technologies). To this end, the paper presents a methodology that enables efficient analysis and enrichment of a large collection of cultural images covering all the major phases and tasks. The proposed method is applied and tested using a case study on cultural image collections from the Europeana platform. The paper further presents the analysis of the case study, the challenges, the lessons learned, and promising future research areas on the topic.

scholarly journals A Model Proposal For Digital Twin Development: Essential Oil Extraction Perspective

2021 ◽  
Author(s):  
Matheus Antonio Nogueira de Andrade ◽  
Herman Augusto Lepikson ◽  
Carlos Alberto Tosta Machado
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Essential Oil ◽  
Hybrid Control ◽  
Oil Extraction ◽  
Industrial Processes ◽  
Yield Increase ◽  
Digital Twins ◽  
Time Simulation

Abstract Introduction: Digital twins are becoming a powerful tool to enhance industrial processes worldwide. This paper proposes a model for the creation of industrial processes’ digital twins using a steam distillation process for essential oil extraction as a case study. Case Description: A grey box modeling is suggested combining a machine learning based model with physical modeling to improve the process. Real time simulation and a hybrid control strategy are used, linked to reinforcement learning and proportional integral derivative control, focusing on the yield increase and optimization. Computer Vision and Artificial Intelligence enhancements were suggested. Discussion and Evaluation: Digital twins, in combination with Artificial Intelligence can be of great help to support companies with the decision-making challenges. Furthermore, some benefits that Artificial Intelligence can bring to the process were enlightened. Computer Vision approaches were also discussed. Conclusions: A creation method is elaborated to support other applications of digital twins in industrial processes in the future. In order to apply it to different processes, generalization capabilities must be proved.

Ground Probing Radar prospecting and urban cultural heritage: the case study of San Pietro dei Pescatori church in Cagliari, Italy

2013 ◽  
Vol 6 (2) ◽  
pp. 18-27 ◽  
Author(s):  
L. Piroddi ◽  
S. Calcina ◽  
A. Trogu ◽  
W. Bakinowska ◽  
M.L. Casnedi ◽  
...  
Keyword(s):  
Cultural Heritage

МЕТОДЫ ДОСТИЖЕНИЯ МАКСИМАЛЬНОЙ ЭФФЕКТИВНОСТИ ПЛАТФОРМЫ ПРОТОТИПИРОВАНИЯ ВЫСОКОПРОИЗВОДИТЕЛЬНЫХ СИСТЕМ НА КРИСТАЛЛЕ НА ЗАДАЧАХ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА

2020 ◽  
Vol 96 (3s) ◽  
pp. 585-588
Author(s):  
С.Е. Фролова ◽  
Е.С. Янакова
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Computer Vision ◽  
High Performance ◽  
Systems On Chip ◽  
High Performance Systems ◽  
On Chip ◽  
Network Technologies ◽  
Neural Network Technologies

Предлагаются методы построения платформ прототипирования высокопроизводительных систем на кристалле для задач искусственного интеллекта. Изложены требования к платформам подобного класса и принципы изменения проекта СнК для имплементации в прототип. Рассматриваются методы отладки проектов на платформе прототипирования. Приведены результаты работ алгоритмов компьютерного зрения с использованием нейросетевых технологий на FPGA-прототипе семантических ядер ELcore. Methods have been proposed for building prototyping platforms for high-performance systems-on-chip for artificial intelligence tasks. The requirements for platforms of this class and the principles for changing the design of the SoC for implementation in the prototype have been described as well as methods of debugging projects on the prototyping platform. The results of the work of computer vision algorithms using neural network technologies on the FPGA prototype of the ELcore semantic cores have been presented.

scholarly journals An emotions-informed approach for digital documentation of rural heritage landscapes: Baojiatun, a traditional tunpu village in Guizhou, China

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Jane-Heloise Nancarrow ◽  
Chen Yang ◽  
Jing Yang
Keyword(s):  
Cultural Heritage ◽  
Interpersonal Relationships ◽  
Local Community ◽  
Heritage Management ◽  
Guizhou Province ◽  
Holistic Understanding ◽  
Digital Documentation ◽  
Multi Level ◽  
Emotional Value ◽  
Digital Survey

AbstractThe application of digital technologies has greatly improved the efficiency of cultural heritage documentation and the diversity of heritage information. Yet the adequate incorporation of cultural, intangible, sensory or experimental elements of local heritage in the process of digital documentation, and the deepening of local community engagement, remain important issues in cultural heritage research. This paper examines the heritage landscape of tunpu people within the context of digital conservation efforts in China and the emergence of emotions studies as an evaluative tool. Using a range of data from the Ming-era village of Baojiatun in Guizhou Province, this paper tests an exploratory emotions-based approach and methodology, revealing shifting interpersonal relationships, experiential and praxiological engagement with the landscape, and emotional registers within tunpu culture and heritage management. The analysis articulates distinctive asset of emotional value at various scales and suggests that such approaches, applied within digital documentation contexts, can help researchers to identify multi-level heritage landscape values and their carriers. This methodology can provide more complete and dynamic inventories to guide digital survey and representation; and the emotions-based approach also supports the integration of disparate heritage aspects in a holistic understanding of the living landscape. Finally, the incorporation of community participation in the process of digital survey breaks down boundaries between experts and communities and leads to more culturally appropriate heritage records and representations.

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