Abstract
The geometric documentation of a cultural heritage site is a demanding task due to the complex morphology of the objects as well as the need for large scale performance. The use of two rapidly evolving approaches, the Unmanned Aerial Vehicles (UAV) and the Dense Image Matching is an attractive solution to extract quality photogrammetric products like orthoimages, 3D point clouds, etc. In this paper, an orthoimage of Asclepieion at the Ancient Messene is produced using UAV imagery and applying Dense Image Matching and its quality and accuracy are compared to the products of a traditional photogrammetric procedure.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Hullo, J.F., Grussenmeyer, P., Fares, S.: Photogrammetry and Dense Stereo Matching Approach Applied to the Documentation of the Cultural Heritage Site of Kilwa (Saudi Arabia). In: 22nd CIPA Symposium, Kyoto, Japan (2009)
Martos, A., Navarro, S., Lerma, J.L., Rodriguez, S., Rodriguez, S., Rodriguez, J.: Orthoware: Software Tool for Image Based Architectural Photogrammetry. In: Proceedings of the 14th International Conference on Virtual Systems and Multimedia, Cyprus, pp. 32–39 (2008)
Pérez, A., Cachero, R., Navarro, S., Jordá, F., López, D., Lerma, J.L., Martos, A.: Digital Reconstruction of the Church of San Ildefonso in Zamora (Spain) using Orthoware. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (IAPRSSIS), Trendo, Italy, vol. 38-5/W16, pp. 61–68 (2011)
Stentoumis, C., Grammatikopoulos, L., Kalisperakis, I., Petsa, E., Karras, G.: A Local Adaptive Approach for Dense Stereo Matching in Architectural Scene Reconstruction. In: 5th International Workshop on 3D Virtual Reconstruction and Visualization of Complex Architectures (3D-ARCH 2013) Trento, Italy (2013)
Nelson, E.A., Dunn, I.T., Forrester, J., Gambin, T., Clark, C.M., Wood, Z.J.: Surface Reconstruction of Ancient Water Storage Systems - An Approach for Sparse 3D Sonar Scans and Fused Stereo Images. In: 9th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Lisbon, Portugal (2014)
Brown, M., Burschka, D., Hager, G.: Advances in Computational Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(8), 993–1008 (2003)
Haala, N.: Multiray Photogrammetry and Dense Image Matching. In: Fritsch, D. (ed.) Photogrammetric Week 2011, pp. 185–195. Wichmann, Berlin (2011)
Zabih, R., Woodfill, J.: Non-parametric local transforms for computing visual correspondence. In: Eklundh, J.-O. (ed.) ECCV 1994. LNCS, vol. 801, pp. 151–158. Springer, Heidelberg (1994)
Hirschmüller, H., Scharstein, D.: Evaluation of stereo matching costs on images with radiometric differences. IEEE Transactions on Pattern Analysis and Machine Intelligence 31(9), 1582–1599 (2009)
Viola, P., Wells, W.M.: Alignment by maximization of mutual information. International Journal of Computer Vision 24(2), 137–154 (1997)
Hirschmüller, H.: Stereo Vision in Structured Environments by Consistent Semi-Global Matching. In: IEEE Conference on Computer Vision and Pattern Recognition, New York, USA (2006)
Bradski, G., Kaehler, A.: Learning OpenCV. O’Reilly Media, USA (2008)
Scharstein, D., Szeliski, R.: A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision 47(1), 7–42 (2002)
Stentoumis, C., Grammatikopoulos, L., Kalisperakis, I., Karras, G.: Implementing an Adaptive Approach for Dense Stereo Matching. In: IAPRSSIS, Part 5, vol. 38, pp. 309–314 (2012)
Kolmogorov, V., Zabih, R.: Computing visual correspondence with occlusions using graph cuts. In: IEEE Conference on Computer Vision, pp. 508–515 (2001)
Veksler, O.: Stereo correspondence by dynamic programming on a tree. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 384–390 (2005)
Sun, J., Zheng, N.N., Shum, H.Y.: Stereo matching using belief propagation. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(7), 787–800 (2003)
Hirschmüller, H.: Stereo processing by Semiglobal matching and mutual information. IEEE Transactions on Pattern Analysis and Machine Intelligence 30(2), 328–341 (2008)
Zhang, K., Lu, J., Lafruit, G.: Cross-based local stereo matching using orthogonal integral images. IEEE Transactions on Circuits and Systems for Video Technology 19(7), 1073–1079 (2009)
Mei, X., Sun, X., Zhou, M., Jiao, S., Wang, H., Zhang, X.: On building an accurate stereo matching system on graphics hardware. In: ICCV Workshop on GPU in Computer Vision Applications (2011)
Hirschmüller, H.: Accurate and efficient stereo processing by semi-global matching and mutual information. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 807–814 (2005)
Vassilaki, D., Ioannidis, C., Stamos, A.: Multitemporal Data Registration through Global Matching of Networks of Free-form Curves. In: Proceedings of FIG Working Week 2009, Eilat, Israel (2009)
Birchfield, S., Tomasi, C.: Depth discontinuities by pixel-to-pixel stereo. In: Proceedings of the 6th IEEE International Conference on Computer Vision, Mumbai, India, pp. 1073–1080 (1998)
Adam, K.: Geometry of the stereo-pair from calibrated and un-calibrated cameras. Diploma thesis, NTUA, Greece (2011) (in Greek)
Society of Messenian Archaeological Studies, Ancient Messene: The Asclepieion, http://www.ancientmessene.gr/site/monuments_articles_en.php?id=13
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Maltezos, E., Ioannidis, C. (2014). Orthoimage of Asclepieion at the Ancient Messene from UAV Images Applying Dense Image Matching. In: Ioannides, M., Magnenat-Thalmann, N., Fink, E., Žarnić, R., Yen, AY., Quak, E. (eds) Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection. EuroMed 2014. Lecture Notes in Computer Science, vol 8740. Springer, Cham. https://doi.org/10.1007/978-3-319-13695-0_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-13695-0_7
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13694-3
Online ISBN: 978-3-319-13695-0
eBook Packages: Computer ScienceComputer Science (R0)