Tirtha - An Automated Platform to Crowdsource Images and Create 3D Models of Heritage Sites
Article No.: 11, Pages 1 - 15
Abstract
Digital preservation of Cultural Heritage (CH) sites is crucial to protect them against damage from natural disasters or human activities. Creating 3D models of CH sites has become a popular method of digital preservation thanks to advancements in computer vision and photogrammetry. However, the process is time-consuming, expensive, and typically requires specialized equipment and expertise, posing challenges in resource-limited developing countries. Additionally, the lack of an open repository for 3D models hinders research and public engagement with their heritage. To address these issues, we propose Tirtha, a web platform for crowdsourcing images of CH sites and creating their 3D models. Tirtha utilizes state-of-the-art Structure from Motion (SfM) and Multi-View Stereo (MVS) techniques. It is modular, extensible and cost-effective, allowing for the incorporation of new techniques as photogrammetry advances. Tirtha is accessible through a web interface at https://tirtha.niser.ac.in and can be deployed on-premise or in a cloud environment. In our case studies, we demonstrate the pipeline’s effectiveness by creating 3D models of temples in Odisha, India, using crowdsourced images. These models are available for viewing, interaction, and download on the Tirtha website. Our work aims to provide a dataset of crowdsourced images and 3D reconstructions for research in computer vision, heritage conservation, and related domains. Overall, Tirtha is a step towards democratizing digital preservation, primarily in resource-limited developing countries.
References
[1]
Bashar Alsadik. 2022. Crowdsource Drone Imagery - A Powerful Source for the 3D Documentation of Cultural Heritage at Risk. International Journal of Architectural Heritage 16, 7 (2022), 977–987. https://doi.org/10.1080/15583058.2020.1853851 arXiv:https://doi.org/10.1080/15583058.2020.1853851
[2]
Narges Azizifard, Lodewijk Gelauff, Jean-Olivier Gransard-Desmond, Miriam Redi, and Rossano Schifanella. 2022. Wiki Loves Monuments: Crowdsourcing the Collective Image of the Worldwide Built Heritage. J. Comput. Cult. Herit. 16, 1, Article 20 (dec 2022), 27 pages. https://doi.org/10.1145/3569092
[3]
Bálint Balázs, Peter Mooney, Eva Nováková, Lucy Bastin, and Jamal Jokar Arsanjani. 2021. Data Quality in Citizen Science. Springer International Publishing, Cham, 139–157. https://doi.org/10.1007/978-3-030-58278-4_8
[4]
Marcin Barszcz, Jerzy Montusiewicz, Magdalena Paśnikowska-Łukaszuk, and Anna Sałamacha. 2021. Comparative Analysis of Digital Models of Objects of Cultural Heritage Obtained by the “3D SLS” and “SfM” Methods. Applied Sciences 11, 12 (Jun 2021), 5321. https://doi.org/10.3390/app11125321
[5]
Andrew Bevan, Pett Daniel, Bonacchi Chiara, Adi Keinan-Schoonbaert, Daniel Lombraña González, Rachael Sparks, Jennifer Wexler, and Neil Wilkin. 2014. Citizen archaeologists. Online collaborative research about the human past. Human Computation 1, 2 (30 Dec 2014). https://hcjournal.org/index.php/jhc/article/view/23
[6]
Elisa Bonacini, Laura Inzerillo, Marianna Marcucci, Cettina Santagati, and Fabrizio Todisco. 2015. 3D DigitalInvasions: a crowdsourcing project for mobile user generated content. (2015). https://api.core.ac.uk/oai/oai:iris.unipa.it:10447/221377
[7]
Rosie Brigham, Scott Allan Orr, Lyn Wilson, Adam Frost, Matija Strlič, and Josep Grau-Bové. 2022. Using Citizen Heritage Science to Monitor Remote Sites Before and During the First COVID-19 Lockdown: A Comparison of Two Methods. Conservation and Management of Archaeological Sites 0, 0 (2022), 1–16. https://doi.org/10.1080/13505033.2022.2147299 arXiv:https://doi.org/10.1080/13505033.2022.2147299
[8]
Zhiqin Chen, Thomas Funkhouser, Peter Hedman, and Andrea Tagliasacchi. 2023. MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architectures. In The Conference on Computer Vision and Pattern Recognition (CVPR).
[9]
Eugene Ch’ng, Shengdan Cai, Tong Evelyn Zhang, and Fui-Theng Leow. 2019. Crowdsourcing 3D cultural heritage: best practice for mass photogrammetry. Journal of Cultural Heritage Management and Sustainable Development 9, 1 (01 Jan 2019), 24–42. https://doi.org/10.1108/JCHMSD-03-2018-0018
[10]
A. D’Andrea, F. Niccolucci, S. Bassett, and K. Fernie. 2012. 3D-ICONS: World Heritage sites for Europeana: Making complex 3D models available to everyone. In 2012 18th International Conference on Virtual Systems and Multimedia. 517–520. https://doi.org/10.1109/VSMM.2012.6365966
[11]
Hari K. Dhonju, Wen Xiao, Jon P. Mills, and Vasilis Sarhosis. 2018. Share Our Cultural Heritage (SOCH): Worldwide 3D Heritage Reconstruction and Visualization via Web and Mobile GIS. ISPRS International Journal of Geo-Information 7, 9 (2018). https://doi.org/10.3390/ijgi7090360
[12]
H. K. Dhonju, W. Xiao, B. Shakya, J. P. Mills, and V. Sarhosis. 2017. DOCUMENTATION OF HERITAGE STRUCTURES THROUGH GEO-CROWDSOURCING AND WEB-MAPPING. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (2017), 17–21. https://doi.org/10.5194/isprs-archives-XLII-2-W7-17-2017
[13]
Oliver Dietz and Jens Grubert. 2022. Towards Open-Source Web-Based 3D Reconstruction for Non-Professionals. Frontiers in Virtual Reality 2 (2022), 786558. https://doi.org/10.3389/frvir.2021.786558
[14]
Thanh-Nghi Doan and Chuong V. Nguyen. 2023. A low-cost digital 3D insect scanner. Information Processing in Agriculture (2023). https://doi.org/10.1016/j.inpa.2023.03.003
[15]
Anastasios Doulamis, Athanasios Voulodimos, Eftychios Protopapadakis, Nikolaos Doulamis, and Konstantinos Makantasis. 2020. Automatic 3D Modeling and Reconstruction of Cultural Heritage Sites from Twitter Images. Sustainability 12, 10 (2020). https://doi.org/10.3390/su12104223
[16]
Isidora Duric, Ivana Vasiljevic, Miloš Obradovic, Vesna Stojakovic, Jelena Kicanovic, and Ratko Obradovic. 2021. Comparative Analysis of Open-Source and Commercial Photogrammetry Software for Cultural Heritage. https://doi.org/10.52842/conf.ecaade.2021.2.243
[17]
Economic Advisory Council to the Prime Minister. 2023. Monuments of National Importance, India. https://eacpm.gov.in/wp-content/uploads/2023/01/Monuments-of-National-Importance.pdf
[18]
R. Eker, N. Elvanoglu, Z. Ucar, E. Bilici, and A. Aydın. 2022. 3D MODELLING OF A HISTORIC WINDMILL: PPK-AIDED TERRESTRIAL PHOTOGRAMMETRY VS SMARTPHONE APP. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2022 (2022), 787–792. https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-787-2022
[19]
Yasutaka Furukawa and Carlos Hernández. 2015. Multi-View Stereo: A Tutorial. Foundations and Trends® in Computer Graphics and Vision 9, 1-2 (2015), 1–148. https://doi.org/10.1561/0600000052
[20]
Francesco Gherardini, Mattia Santachiara, and Francesco Leali. 2019. Enhancing heritage fruition through 3D virtual models and augmented reality: an application to Roman artefacts. Virtual Archaeology Review 10, 21 (Jul. 2019), 67–79. https://doi.org/10.4995/var.2019.11918
[21]
Mrinmoy Ghorai, Pulak Purkait, Sanchayan Santra, Soumitra Samanta, and Bhabatosh Chanda. 2016. Bishnupur Heritage Image Dataset (BHID): A Resource for Various Computer Vision Applications. In Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing (Guwahati, Assam, India) (ICVGIP ’16). Association for Computing Machinery, New York, NY, USA, Article 80, 8 pages. https://doi.org/10.1145/3009977.3010005
[22]
Mrinmoy Ghorai, Sanchayan Santra, Soumitra Samanta, Pulak Purkait, and Bhabatosh Chanda. 2018. An Image Dataset of Bishnupur Terracotta Temples for Digital Heritage Research. Springer Singapore, Singapore, 269–291. https://doi.org/10.1007/978-981-10-7221-5_13
[23]
Carsten Griwodz, Simone Gasparini, Lilian Calvet, Pierre Gurdjos, Fabien Castan, Benoit Maujean, Gregoire De Lillo, and Yann Lanthony. 2021. AliceVision Meshroom: An Open-Source 3D Reconstruction Pipeline. In Proceedings of the 12th ACM Multimedia Systems Conference (Istanbul, Turkey) (MMSys ’21). Association for Computing Machinery, New York, NY, USA, 241–247. https://doi.org/10.1145/3458305.3478443
[24]
Jeff Howe. 2006. The rise of Crowdsourcing. https://www.wired.com/2006/06/crowds/
[25]
Laura Inzerillo and Cettina Santagati. 2016. Crowdsourcing Cultural Heritage: From 3D Modeling to the Engagement of Young Generations. In Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection. Springer International Publishing, Cham, 869–879.
[26]
Renata Jadresin Milic, Peter McPherson, Graeme McConchie, Thomas Reutlinger, and Sian Singh. 2022. Architectural History and Sustainable Architectural Heritage Education: Digitalisation of Heritage in New Zealand. Sustainability 14, 24 (2022). https://doi.org/10.3390/su142416432
[27]
Eirini Kaldeli, Orfeas Menis-Mastromichalakis, Spyros Bekiaris, Maria Ralli, Vassilis Tzouvaras, and Giorgos Stamou. 2021. CrowdHeritage: Crowdsourcing for Improving the Quality of Cultural Heritage Metadata. Information 12, 2 (2021), 64. https://doi.org/10.3390/info12020064
[28]
Zhaoshuo Li, Thomas Müller, Alex Evans, Russell H. Taylor, Mathias Unberath, Ming-Yu Liu, and Chen-Hsuan Lin. 2023. Neuralangelo: High-Fidelity Neural Surface Reconstruction. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 8456–8465.
[29]
Ziwen Liu, Rosie Brigham, Emily Rosemary Long, Lyn Wilson, Adam Frost, Scott Allan Orr, and Josep Grau-Bové. 2022. Semantic segmentation and photogrammetry of crowdsourced images to monitor historic facades. Heritage Science 10, 1 (19 Feb 2022), 27. https://doi.org/10.1186/s40494-022-00664-y
[30]
Ricardo Martin-Brualla, Noha Radwan, Mehdi S. M. Sajjadi, Jonathan T. Barron, Alexey Dosovitskiy, and Daniel Duckworth. 2021. NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections. In CVPR.
[31]
S. M. Meena, N. K. Abhishek, Anup Ravikumar, Uday Kulkarni, Sunil V. Gurlahosur, and M. Uma. 2021. Crowd Source Framework for Indian Digital Heritage Space. Springer International Publishing, Cham, 123–145. https://doi.org/10.1007/978-3-030-66777-1_6
[32]
F. Menna, E. Nocerino, D. Morabito, E. M. Farella, M. Perini, and F. Remondino. 2017. AN OPEN SOURCE LOW-COST AUTOMATIC SYSTEM FOR IMAGE-BASED 3D DIGITIZATION. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W8 (2017), 155–162. https://doi.org/10.5194/isprs-archives-XLII-2-W8-155-2017
[33]
Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng. 2020. NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis. CoRR abs/2003.08934 (2020). arXiv:2003.08934https://arxiv.org/abs/2003.08934
[34]
Helen C. Miles, Andrew T. Wilson, Frederic Labrosse, Bernard Tiddeman, Seren Griffiths, Ben Edwards, Katharina Moller, Raimund Karl, and Jonathan C. Roberts. 2014. Crowd-Sourced Digitisation of Cultural Heritage Assets. In Proceedings of the 2014 International Conference on Cyberworlds(CW ’14). IEEE Computer Society, USA, 361–368. https://doi.org/10.1109/CW.2014.57
[35]
Helen C. Miles, Andrew T. Wilson, Frédéric Labrosse, Bernard Tiddeman, Seren Griffiths, Ben Edwards, Panagiotis D. Ritsos, Joseph W. Mearman, Katharina Möller, Raimund Karl, and Jonathan C. Roberts. 2015. Alternative Representations of 3D-Reconstructed Heritage Data. J. Comput. Cult. Herit. 9, 1, Article 4 (nov 2015), 18 pages. https://doi.org/10.1145/2795233
[36]
Lorenzo Monti, Giovanni Delnevo, Silvia Mirri, Paola Salomoni, and Franco Callegati. 2018. Digital Invasions Within Cultural Heritage: Social Media and Crowdsourcing. In Smart Objects and Technologies for Social Good. Springer International Publishing, Cham, 102–111.
[37]
Uma Mudenagudi, Syed Altaf Ganihar, and Shankar Setty. 2017. Realistic Walkthrough of Cultural Heritage Sites. Springer Singapore, Singapore, 131–147. https://doi.org/10.1007/978-981-10-5738-0_9
[38]
Štefan Mudička and Roman Kapica. 2023. Digital Heritage, the Possibilities of Information Visualisation through Extended Reality Tools. Heritage 6, 1 (2023), 112–131. https://doi.org/10.3390/heritage6010006
[39]
Niti Aayog. 2020. Improving Heritage Management in India. Niti Aayog. https://www.niti.gov.in/sites/default/files/2020-06/Improving-HeritageManagement-in-India.pdf
[40]
OpenStreetMap contributors. 2023. OpenStreetMap. OpenStreetMap. https://www.openstreetmap.org/
[41]
Jorge Otero. 2021. Heritage Conservation Future: Where We Stand, Challenges Ahead, and a Paradigm Shift. Glob Chall 6, 1 (Oct. 2021), 2100084.
[42]
Onur Özyesil, Vladislav Voroninski, Ronen Basri, and Amit Singer. 2017. A Survey on Structure from Motion. CoRR abs/1701.08493 (2017). arXiv:1701.08493http://arxiv.org/abs/1701.08493
[43]
Anthony Pamart, François Morlet, Livio De Luca, and Philippe Veron. 2020. A Robust and Versatile Pipeline for Automatic Photogrammetric-Based Registration of Multimodal Cultural Heritage Documentation. Remote Sensing 12, 12 (Jun 2020), 2051. https://doi.org/10.3390/rs12122051
[44]
Massimiliano Pepe, Vincenzo Saverio Alfio, and Domenica Costantino. 2022. UAV Platforms and the SfM-MVS Approach in the 3D Surveys and Modelling: A Review in the Cultural Heritage Field. Applied Sciences 12, 24 (2022). https://doi.org/10.3390/app122412886
[45]
Abdul Hannan Qureshi, Wesam Salah Alaloul, Syed Jawad Hussain, Arnadi Murtiyoso, Syed Saad, Khalid Mhmoud Alzubi, Syed Ammad, and Abdullah O. Baarimah. 2023. Evaluation of Photogrammetry Tools following Progress Detection of Rebar towards Sustainable Construction Processes. Sustainability 15, 1 (2023). https://doi.org/10.3390/su15010021
[46]
Hafizur Rahaman and Erik Champion. 2019. To 3D or Not 3D: Choosing a Photogrammetry Workflow for Cultural Heritage Groups. Heritage 2, 3 (Jul 2019), 1835–1851. https://doi.org/10.3390/heritage2030112
[47]
Hafizur Rahaman, Erik Champion, and Mafkereseb Bekele. 2019. From photo to 3D to mixed reality: A complete workflow for cultural heritage visualisation and experience. Digital Applications in Archaeology and Cultural Heritage 13 (2019), e00102. https://doi.org/10.1016/j.daach.2019.e00102
[48]
Nemeh Rihani. 2023. Interactive immersive experience: Digital technologies for reconstruction and experiencing temple of Bel using crowdsourced images and 3D photogrammetric processes. International Journal of Architectural Computing 0, 0 (2023), 14780771231168224. https://doi.org/10.1177/14780771231168224 arXiv:https://doi.org/10.1177/14780771231168224
[49]
Gehan Selim, Monther Jamhawi, Mohamed Gamal Abdelmonem, Shouib Ma’bdeh, and Andrew Holland. 2022. The Virtual Living Museum: Integrating the Multi-Layered Histories and Cultural Practices of Gadara’s Archaeology in Umm Qais, Jordan. Sustainability 14, 11 (May 2022), 6721. https://doi.org/10.3390/su14116721
[50]
A. Somogyi, A. Barsi, B. Molnar, and T. Lovas. 2016. CROWDSOURCING BASED 3D MODELING. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B5 (2016), 587–590. https://doi.org/10.5194/isprs-archives-XLI-B5-587-2016
[51]
E. K. Stathopoulou, A. Georgopoulos, G. Panagiotopoulos, and D. Kaliampakos. 2015. Crowdsourcing Lost Cultural Heritage. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences II-5/W3 (2015), 295–300. https://doi.org/10.5194/isprsannals-II-5-W3-295-2015
[52]
E.-K. Stathopoulou, M. Welponer, and F. Remondino. 2019. OPEN-SOURCE IMAGE-BASED 3D RECONSTRUCTION PIPELINES: REVIEW, COMPARISON AND EVALUATION. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W17 (2019), 331–338. https://doi.org/10.5194/isprs-archives-XLII-2-W17-331-2019
[53]
Kathleen Tuite, Noah Snavely, Dun-yu Hsiao, Nadine Tabing, and Zoran Popovic. 2011. PhotoCity: Training Experts at Large-Scale Image Acquisition through a Competitive Game. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Vancouver, BC, Canada) (CHI ’11). Association for Computing Machinery, New York, NY, USA, 1383–1392. https://doi.org/10.1145/1978942.1979146
[54]
UNESCO. 2015. Policy Document on World Heritage and Sustainable Development. UNESCO. https://whc.unesco.org/document/139747
[55]
Giuseppina Vacca. 2023. 3D Survey with Apple LiDAR Sensor—Test and Assessment for Architectural and Cultural Heritage. Heritage 6, 2 (Feb 2023), 1476–1501. https://doi.org/10.3390/heritage6020080
[56]
Matthew L. Vincent. 2017. Crowdsourced Data for Cultural Heritage. Springer International Publishing, Cham, 79–91. https://doi.org/10.1007/978-3-319-65370-9_5
[57]
Matthew L. Vincent, Mariano Flores Gutierrez, Chance Coughenour, Victor Manuel, Lopez-Menchero Bendicho, Fabio Remondino, and Dieter Fritsch. 2015. Crowd-sourcing the 3D digital reconstructions of lost cultural heritage. In 2015 Digital Heritage, Vol. 1. 171–172. https://doi.org/10.1109/DigitalHeritage.2015.7413863
[58]
Alexandre Vrubel, Olga R. P. Bellon, and Luciano Silva. 2009. A 3D reconstruction pipeline for digital preservation. In 2009 IEEE Conference on Computer Vision and Pattern Recognition. 2687–2694. https://doi.org/10.1109/CVPR.2009.5206586
[59]
B. Wang, G. Z. Dane, and B. de Vries. 2018. INCREASING AWARENESS FOR URBAN CULTURAL HERITAGE BASED ON 3D NARRATIVE SYSTEM. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W10 (2018), 215–221. https://doi.org/10.5194/isprs-archives-XLII-4-W10-215-2018
[60]
Wikipedia contributors. 2023. Wikipedia. Wikipedia. https://en.wikipedia.org/
[61]
Sidi Yang, Tianhe Wu, Shuwei Shi, Shanshan Lao, Yuan Gong, Mingdeng Cao, Jiahao Wang, and Yujiu Yang. 2022. MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 1191–1200.
[62]
Zooniverse contributors. 2023. Zooniverse. Zooniverse. https://www.zooniverse.org/
Index Terms
- Tirtha - An Automated Platform to Crowdsource Images and Create 3D Models of Heritage Sites
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October 2023
244 pages
ISBN:9798400703249
DOI:10.1145/3611314
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- La fondation Dassault Systèmes India
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Web3D '23: The 28th International ACM Conference on 3D Web Technology
October 9 - 11, 2023
San Sebastian, Spain
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