Abstract
This paper introduces a novel approach for optimizing image capture using View-Planning (VP) to enhance Gaussian splatting for 3D reconstruction of archaeological sites, specifically focusing on Castellaraccio di Monteverdi. Traditional photogrammetry often produces over-smoothed models with artifacts. Our proposed approach leverages VP planning to select optimal viewpoints, ensuring comprehensive image coverage. We integrate this with Gaussian splatting which outputs highly-realistic 3D reconstructions. Initial evaluations on sample datasets demonstrate the potential of VP-enhanced Gaussian splatting to surpass traditional methods in terms of quality. The paper details our approach, discusses the challenges of 3D reconstruction without VP, and outlines our ongoing and future work, including upcoming tests at Castellaraccio di Monteverdi. Our findings aim to contribute to the field of archaeological documentation and analysis, supporting better preservation and understanding of historical sites.
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References
Agisoft Metashape: Agisoft Metashape—agisoft.com. https://www.agisoft.com. Accessed 15 May 2024
Polycam - LiDAR & 3D Scanner for iPhone & Android—poly.cam. http://poly.cam. Accessed 15 May 2024
Frequency-importance Gaussian splatting for real-time lightweight radiance field rendering - scientific figure on researchgate (2024). https://www.researchgate.net/figure/Pipeline-of-Gaussian-Splatting-Pipeline-of-Gaussian-Splatting-First-initial-sample_fig4_378904778. Accessed 15 May 2024
Barron, J.T., Mildenhall, B., Tancik, M., Hedman, P., Martin-Brualla, R., Srinivasan, P.P.: Mip-NeRF: a multiscale representation for anti-aliasing neural radiance fields. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 5855–5864 (2021)
Bradski, G.: The OpenCV library. Dr. Dobb’s J. Softw. Tools Prof. Programmer 25(11), 120–123 (2000)
Bruno, F., Bruno, S., De Sensi, G., Luchi, M.L., Mancuso, S., Muzzupappa, M.: From 3D reconstruction to virtual reality: a complete methodology for digital archaeological exhibition. J. Cult. Herit. 11(1), 42–49 (2010). https://doi.org/10.1016/j.culher.2009.02.006
Colomina, I., Molina, P.: Unmanned aerial systems for photogrammetry and remote sensing: a review. ISPRS J. Photogramm. Remote. Sens. 92, 79–97 (2014). https://doi.org/10.1016/j.isprsjprs.2014.02.013
Connolly, C.: The determination of next best views. In: Proceedings. 1985 IEEE International Conference on Robotics and Automation, vol. 2, pp. 432–435 (1985). https://doi.org/10.1109/ROBOT.1985.1087372
Dawn, S., Biswas, P.: Technologies and methods for 3D reconstruction in archaeology. In: Thampi, S.M., Marques, O., Krishnan, S., Li, K.-C., Ciuonzo, D., Kolekar, M.H. (eds.) SIRS 2018. CCIS, vol. 968, pp. 443–453. Springer, Singapore (2019). https://doi.org/10.1007/978-981-13-5758-9_38
De Reu, J., De Smedt, P., Herremans, D., Van Meirvenne, M., Laloo, P., De Clercq, W.: On introducing an image-based 3D reconstruction method in archaeological excavation practice. J. Archaeol. Sci. 41, 251–262 (2014). https://doi.org/10.1016/j.jas.2013.08.020
Dias, P., Matos, M., Santos, V.: 3D reconstruction of real world scenes using a low-cost 3D range scanner. Comput.-Aided Civil Infrastruct. Eng. 21(7), 486–497 (2006). https://doi.org/10.1111/j.1467-8667.2006.00453.x
Gomes, L., Bellon, O.R.P., Silva, L.: 3D reconstruction methods for digital preservation of cultural heritage: a survey. Pattern Recogn. Lett. 50, 3–14 (2014)
Green, S., Bevan, A., Shapland, M.: A comparative assessment of structure from motion methods for archaeological research. J. Archaeol. Sci. 46, 173–181 (2014). https://doi.org/10.1016/j.jas.2014.02.030. https://www.sciencedirect.com/science/article/pii/S030544031400079X
Gupta, T., Li, H.: Indoor mapping for smart cities an affordable approach: using Kinect sensor and zed stereo camera. In: 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), pp. 1–8 (2017). https://doi.org/10.1109/IPIN.2017.8115909
Karaman, S., Frazzoli, E.: Sampling-based algorithms for optimal motion planning. Int. J. Rob. Res. 30(7), 846–894 (2011). https://doi.org/10.1177/0278364911406761
Kavraki, L.E., Svestka, P., Latombe, J.C., Overmars, M.H.: Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Trans. Robot. Autom. 12(4), 566–580 (1996)
Kazhdan, M., Bolitho, M., Hoppe, H.: Poisson surface reconstruction. In: Proceedings of the Fourth Eurographics Symposium on Geometry Processing, vol. 7 (2006)
Kazhdan, M., Chuang, M., Rusinkiewicz, S., Hoppe, H.: Poisson surface reconstruction with envelope constraints. Comput. Graph. Forum 39(5), 173–182 (2020). https://doi.org/10.1111/cgf.14077
Kerbl, B., Kopanas, G., Leimkuehler, T., Drettakis, G.: 3D Gaussian splatting for real-time radiance field rendering. ACM Trans. Graph. 42(4), 1–14 (2023). https://doi.org/10.1145/3592433
Koutsoudis, A., Vidmar, B., Ioannakis, G.A., Arnaoutoglou, F., Pavlidis, G., Chamzas, C.: Multi-image 3D reconstruction data evaluation. J. Cult. Heritage 15, 73–79 (2014). https://api.semanticscholar.org/CorpusID:135535640
Kuffner, J.J., LaValle, S.M.: RRT-connect: an efficient approach to single-query path planning. In: Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No. 00CH37065), vol. 2, pp. 995–1001. IEEE (2000)
Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: NeRF: representing scenes as neural radiance fields for view synthesis (2020). https://doi.org/10.48550/ARXIV.2003.08934
Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: NeRF: representing scenes as neural radiance fields for view synthesis. Commun. ACM 65(1), 99–106 (2021)
Neubauer, W.: GIS in archaeology the interface between prospection and excavation. Archaeol. Prospect. 11(3), 159–166 (2004). https://doi.org/10.1002/arp.231
Peralta, D., Casimiro, J., Nilles, A.M., Aguilar, J.A., Atienza, R., Cajote, R.: Next-best view policy for 3D reconstruction. In: Bartoli, A., Fusiello, A. (eds.) ECCV 2020. LNCS, vol. 12538, pp. 558–573. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-66823-5_33
Sanders, J., Kandrot, E.: CUDA by Example: An Introduction to General-Purpose GPU Programming. Addison-Wesley Professional (2010)
Sansoni, G., Trebeschi, M., Docchio, F.: State-of-the-art and applications of 3D imaging sensors in industry, cultural heritage, medicine, and criminal investigation. Sensors 9(1), 568–601 (2009). https://doi.org/10.3390/s90100568
Schönberger, J.L., Frahm, J.M.: Structure-from-motion revisited. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2016)
Sebastiani, A.: Digital artifacts and landscapes. Experimenting with placemaking at the IMPERO project. Heritage 4(1), 281–303 (2021)
Torr, P.H.S., Zisserman, A.: Feature based methods for structure and motion estimation. In: Triggs, B., Zisserman, A., Szeliski, R. (eds.) IWVA 1999. LNCS, vol. 1883, pp. 278–294. Springer, Heidelberg (2000). https://doi.org/10.1007/3-540-44480-7_19
Turkar, Y., Aluckal, C., De, S., Turkar, V., Agarwadkar, Y.: Generative-network based multimedia super-resolution for UAV remote sensing. In: IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, pp. 527–530 (2022). https://doi.org/10.1109/IGARSS46834.2022.9884486
Verhoeven, G.J.J., Loenders, J., Vermeulen, F., Docter, R.: Helikite aerial photography a versatile means of unmanned, radio controlled, low-altitude aerial archaeology. Archaeol. Prospect. 16(2), 125–138 (2009). https://doi.org/10.1002/arp.353
Yang, M.D., Chao, C.F., Huang, K.S., Lu, L.Y., Chen, Y.P.: Image-based 3D scene reconstruction and exploration in augmented reality. Autom. Constr. 33, 48–60 (2013)
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Turkar, Y., Aluckal, C., Adhivarahan, C., Sebastiani, A., Dantu, K. (2024). A View-Planning Approach to 3D Reconstruction. In: De Paolis, L.T., Arpaia, P., Sacco, M. (eds) Extended Reality. XR Salento 2024. Lecture Notes in Computer Science, vol 15029. Springer, Cham. https://doi.org/10.1007/978-3-031-71710-9_27
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