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Automatic 3D Modeling and Reconstruction of Cultural Heritage Sites from Twitter Images

Author

Listed:
  • Anastasios Doulamis

    (School of Rural and Surveying Engineering, National Technical University of Athens, 15780 Athens, Greece)

  • Athanasios Voulodimos

    (Department of Informatics and Computer Engineering, University of West Attica, 12243 Athens, Greece)

  • Eftychios Protopapadakis

    (School of Rural and Surveying Engineering, National Technical University of Athens, 15780 Athens, Greece
    Department of Informatics and Computer Engineering, University of West Attica, 12243 Athens, Greece)

  • Nikolaos Doulamis

    (School of Rural and Surveying Engineering, National Technical University of Athens, 15780 Athens, Greece)

  • Konstantinos Makantasis

    (Institute of Digital Games, University of Malta, VLT 1216 Valletta, Malta)

Abstract

This paper presents an approach for leveraging the abundance of images posted on social media like Twitter for large scale 3D reconstruction of cultural heritage landmarks. Twitter allows users to post short messages, including photos, describing a plethora of activities or events, e.g., tweets are used by travelers on vacation, capturing images from various cultural heritage assets. As such, a great number of images are available online, able to drive a successful 3D reconstruction process. However, reconstruction of any asset, based on images mined from Twitter, presents several challenges. There are three main steps that have to be considered: (i) tweets’ content identification, (ii) image retrieval and filtering, and (iii) 3D reconstruction. The proposed approach first extracts key events from unstructured tweet messages and then identifies cultural activities and landmarks. The second stage is the application of a content-based filtering method so that only a small but representative portion of cultural images are selected to support fast 3D reconstruction. The proposed methods are experimentally evaluated using real-world data and comparisons verify the effectiveness of the proposed scheme.

Suggested Citation

  • Anastasios Doulamis & Athanasios Voulodimos & Eftychios Protopapadakis & Nikolaos Doulamis & Konstantinos Makantasis, 2020. "Automatic 3D Modeling and Reconstruction of Cultural Heritage Sites from Twitter Images," Sustainability, MDPI, vol. 12(10), pages 1-18, May.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:10:p:4223-:d:361191
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    Citations

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    Cited by:

    1. Minos-Athanasios Karyotakis & Nikos Antonopoulos, 2021. "Web Communication: A Content Analysis of Green Hosting Companies," Sustainability, MDPI, vol. 13(2), pages 1-15, January.
    2. Michail D. Papamichail & Andreas L. Symeonidis, 2021. "Data-Driven Analytics towards Software Sustainability: The Case of Open-Source Multimedia Tools on Cultural Storytelling," Sustainability, MDPI, vol. 13(3), pages 1-16, January.
    3. Luciana Randazzo & Matteo Collina & Michela Ricca & Loris Barbieri & Fabio Bruno & Anna Arcudi & Mauro F. La Russa, 2020. "Damage Indices and Photogrammetry for Decay Assessment of Stone-Built Cultural Heritage: The Case Study of the San Domenico Church Main Entrance Portal (South Calabria, Italy)," Sustainability, MDPI, vol. 12(12), pages 1-12, June.
    4. Marina Eirini Stamatiadou & Iordanis Thoidis & Nikolaos Vryzas & Lazaros Vrysis & Charalampos Dimoulas, 2021. "Semantic Crowdsourcing of Soundscapes Heritage: A Mojo Model for Data-Driven Storytelling," Sustainability, MDPI, vol. 13(5), pages 1-19, March.

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