Digital Restoration of Cultural Heritage With Data-Driven Computing: A Survey
Digitized methodologies in the recent era contribute to various fields of automation that used to hold different interests and meanings of human life. Buildings with historical significance, cultural values, and beliefs are becoming an interdisciplinary field of interest, engaging more computer scie...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10138172/ |
| _version_ | 1797808449609793536 |
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| author | Arkaprabha Basu Sandip Paul Sreeya Ghosh Swagatam Das Bhabatosh Chanda Chakravarthy Bhagvati Vaclav Snasel |
| author_facet | Arkaprabha Basu Sandip Paul Sreeya Ghosh Swagatam Das Bhabatosh Chanda Chakravarthy Bhagvati Vaclav Snasel |
| author_sort | Arkaprabha Basu |
| collection | DOAJ |
| description | Digitized methodologies in the recent era contribute to various fields of automation that used to hold different interests and meanings of human life. Buildings with historical significance, cultural values, and beliefs are becoming an interdisciplinary field of interest, engaging more computer scientists nowadays. Such structures need more attention towards reconstructing their values using a flavor of computerized tools instead of brickwork directly. Due to the wear of time, the tiles and engravings of most of the historical monuments are on the verge of ruin, endangering significant historical values. In this survey, we rebuild the values by delving deep into the device and methodologies by providing a comprehensive understanding of emerging fields and some experimental decisions. We discuss heritage restoration from some essential papers on 3D reconstruction, image inpainting, IoT-based methods, genetic algorithms, and image processing. The survey explains Machine Learning, Deep Learning, and Computer Vision-based methods for various restoration tasks in the related field. We divide this into certain parts contributing to different fields that restore cultural heritage. Moreover, we infer that the techniques will be faster, cheaper, and more beneficial to the context of image reconstruction in the near future. |
| first_indexed | 2024-03-13T06:37:40Z |
| format | Article |
| id | doaj.art-04dba8a5019b4ea6a50a4dd112407124 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-13T06:37:40Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-04dba8a5019b4ea6a50a4dd1124071242023-06-08T23:00:50ZengIEEEIEEE Access2169-35362023-01-0111539395397710.1109/ACCESS.2023.328063910138172Digital Restoration of Cultural Heritage With Data-Driven Computing: A SurveyArkaprabha Basu0https://orcid.org/0000-0003-0136-0887Sandip Paul1Sreeya Ghosh2https://orcid.org/0000-0002-2414-7205Swagatam Das3https://orcid.org/0000-0001-6843-4508Bhabatosh Chanda4Chakravarthy Bhagvati5Vaclav Snasel6https://orcid.org/0000-0002-9600-8319Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, IndiaKolaghat Government Polytechnic, Kolaghat, IndiaElectronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, IndiaUniversity of Hyderabad, Hyderabad, IndiaIndian Institute of Information Technology at Kalyani, Kalyani, IndiaUniversity of Hyderabad, Hyderabad, IndiaVSB–Technical University of Ostrava, Ostrava, Czech RepublicDigitized methodologies in the recent era contribute to various fields of automation that used to hold different interests and meanings of human life. Buildings with historical significance, cultural values, and beliefs are becoming an interdisciplinary field of interest, engaging more computer scientists nowadays. Such structures need more attention towards reconstructing their values using a flavor of computerized tools instead of brickwork directly. Due to the wear of time, the tiles and engravings of most of the historical monuments are on the verge of ruin, endangering significant historical values. In this survey, we rebuild the values by delving deep into the device and methodologies by providing a comprehensive understanding of emerging fields and some experimental decisions. We discuss heritage restoration from some essential papers on 3D reconstruction, image inpainting, IoT-based methods, genetic algorithms, and image processing. The survey explains Machine Learning, Deep Learning, and Computer Vision-based methods for various restoration tasks in the related field. We divide this into certain parts contributing to different fields that restore cultural heritage. Moreover, we infer that the techniques will be faster, cheaper, and more beneficial to the context of image reconstruction in the near future.https://ieeexplore.ieee.org/document/10138172/Cultural heritage3D reconstructionclassificationgenerative adversarial networkbuilding information modelinginpainting |
| spellingShingle | Arkaprabha Basu Sandip Paul Sreeya Ghosh Swagatam Das Bhabatosh Chanda Chakravarthy Bhagvati Vaclav Snasel Digital Restoration of Cultural Heritage With Data-Driven Computing: A Survey IEEE Access Cultural heritage 3D reconstruction classification generative adversarial network building information modeling inpainting |
| title | Digital Restoration of Cultural Heritage With Data-Driven Computing: A Survey |
| title_full | Digital Restoration of Cultural Heritage With Data-Driven Computing: A Survey |
| title_fullStr | Digital Restoration of Cultural Heritage With Data-Driven Computing: A Survey |
| title_full_unstemmed | Digital Restoration of Cultural Heritage With Data-Driven Computing: A Survey |
| title_short | Digital Restoration of Cultural Heritage With Data-Driven Computing: A Survey |
| title_sort | digital restoration of cultural heritage with data driven computing a survey |
| topic | Cultural heritage 3D reconstruction classification generative adversarial network building information modeling inpainting |
| url | https://ieeexplore.ieee.org/document/10138172/ |
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