Overview of Available Open-Source Photogrammetric Software, its Use and Analysis
Main Article Content
Abstract
The current technological era provides a wide range of geodetic procedures and methods to document the actual state of objects on the Earth surface and at the same time course and shape of surface itself. Digital photogrammetry is one of these technologies, it allows the use of methods such as single-image photogrammetry, stereo photogrammetry (optical scanning), convergent imaging and SfM method (structure-from-motion) with final data in the form of point clouds, digital spatial models, orthophotos and other derived documents. Similar outputs can be obtained also by other technologies, mainly by terrestrial laser scanning, whilst each of the two technologies offers certain advantages and disadvantages. Especially purchasing and operating costs are one of the major drawbacks of laser scanning (while being an advantage of photogrammetry). In recent years, there has been a significant increase in development and creation of new, freely accessible (open-source) photogrammetric software, thus reducing these financial demands even more. The aim of this paper is to provide a basic overview of some of the most suitable open-source photogrammetric software and point out their strengths and weaknesses.
Article Details
Section
This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.
Copyrights for articles published in IJIER journals are retained by the authors, with first publication rights granted to the journal. The journal/publisher is not responsible for subsequent uses of the work. It is the author's responsibility to bring an infringement action if so desired by the author for more visit Copyright & License.
How to Cite
References
Agarval, S. et al. Bundle adjustment in the large. European Conference on Computer Vision. 2010, Greece, Crete. Pp. II: 29–42, 2010. DOI: https://doi.org/10.1007/978-3-642-15552-9_3
Astre, H. Photosynth Toolkit. Ver. 11. 2010. Available at http://www.visual-experiments.com/demos/photosynthtoolkit/
Autodesk. 123D Catch. USA, 2013. Available at http://www.123dapp.com/catch
Bartoš, K. The use of open-source photogrammetric software for the needs of documentation of cultural heritage, its analysis and accuracy = Využitie open-source fotogrametrických softvérov pre potreby pamiatkovej dokumentácie, ich analýza a presnosť. PhD thesis. Košice: The Technical university of Košice, Faculty of mining, ecology, process control and geotechnology. 2013. 132 p.
Fraštia, M. Fotogrametria v procese dokumentácie pamiatok. Bardkontakt 2009. Problematika mestských pamiatkových centier. Bardejov, 2009, Mesto Bardejov, ISBN 978-80-970188-9-4, s. 30-35.
Fraštia, M. Laserové verzus optické skenovanie skalných masívov. Mineralia Slovaca. Vol. 44, Issue 2. 2012.
Furukawa, Y. et al. Towards Internet-scale Multi-view Stereo. IEEE Conference on Computer Vision and Pattern Recognition. USA, San Francisco, 2010. pp. 1434-1441. DOI: https://doi.org/10.1109/CVPR.2010.5539802
Furukawa, Y., Ponce, J. Acurate, Dense, and Robust Multi-View Stereopsis. IEEE Transactions On Pattern Analysis and Machine Intelligence. August 2010. Vol. 32, Issue 8, pp. 1362-1376.[9] Furukawa, Y., Ponce, J. Accurate Camera Calibration from Multi-View Stereo and Bundle Adjustment. IEEE conference on Computer Vision and Pattern Recognition. USA, 2008.
Gašincová, S., Gašinec, J., Weiss, G., Labant, S.: Application of robust estimation methods for the analysis of outlier measurements. GeoScienceEngineering. Vol. 57, No. 3. 2001. pp. 14-29. DOI: https://doi.org/10.2478/v10205-011-0007-1
Goesele, M. et al. Multiview stereo for community photo collections. IEEE International Conference on Computer Vision. Rio de Janeiro, 2007. pp. 1-8. DOI: https://doi.org/10.1109/ICCV.2007.4408933
Gruen, A., Baltsavias, E. Geometrically Constrained Multiphoto Matching. Photogrammetric Engineering & Remote Sensing. Volume 54, pp. 633-641. 1988
Jancosek, M., Pajdla, T. Multi-View Reconstruction Preserving Weakly-Supported Surfaces, CVPR 2011 - IEEE Conference on Computer Vision and Pattern Recognition, Colorado Springs, USA, 2011. DOI: https://doi.org/10.1109/CVPR.2011.5995693
Kersten, P. T. 3D Point Clouds through Image-Based Low-Cost systems. CLGE General Assembly, Hannover, Germany, 2012.
Kraus, K. Photogrammetry, Volume 1, Fundamentals and Standard Processes. Bonn: Ferd. Dümmlers Verlag, 1993. ISBN 3-427-78684-6
Kraus, K. Photogrammetry, Geometry from images and laser scans. Berlin, New York, Walter de Gruyter, 2004. ISBN 978-3-11-019007-6
Lourakis, M. I. A., Argyros, A. A. SBA: A Software Package for Generic Sparse Bundle Adjustment. ACM Trans. Math. Softw. 36, 1, Article 2 (March 2009), 30 p. DOI: https://doi.org/10.1145/1486525.1486527
Lowe, G. David. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision. October, 2004, Vol.60, No 1. DOI: https://doi.org/10.1023/B:VISI.0000029664.99615.94
Luhmann, T., Robson, S., Kyle, S., Harley, I. Close Range Photogrammetry, Principles, Methods and Applications. Dunbeath, Scotland, UK, Whittles Publishing, 2006. ISBN 1-870325-50-8
MICROSOFT. Photosynth. USA, 2012. Available at http://photosynth.net/
Pierrot-Deseilligny, M., Paparoditis, N. A multiresolution and optimization-based image matching approach: an application to surface reconstruction from SPT5-HRS stereo imagery. Int. Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. 36-1/W41. Ankara, Turkey, 2006.
Pollefeys, M. et al. Visual modeling with a hand-held camera. International Journal of Computer Vision 59(3), 207-232, 2004. DOI: https://doi.org/10.1023/B:VISI.0000025798.50602.3a
Rákay, Š. ml.: Measurement and volume determination of the irregular solids. 1st ed. Bíbor Publisher, Miskolc. 2013. 84 p.
Remondino, F. et al. Low-cost and open-source solutions for automated image orientation – A critical overview. Proc. EuroMed 2012 Conference, M. Ioannides et al. (Eds.), LNCS 7616, pp. 40-54. Springer, Heidelberg DOI: https://doi.org/10.1007/978-3-642-34234-9_5
Remondino, F., Fraser, C. Digital camera calibration methods: considerations and comparisons. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences. Volume 36, Part 5. Germany, 2006.
Sabo, J., Bálint, J.: Possibilities of using GNSS in air navigation. New trends in civil aviation 2013, Akademické nakladatelství CERM. 2013. pp. 84-86.
Snavely, N. Bundler. USA, 2012. Available at http://phototour.cs.washington.edu/bundler/#S3
Snavely, N. et al. Photo Tourism: Exploring photo collections in 3D. ACM Transactions on Graphics (SIGGRAPH Proceedings). July, 2006. Vol. 25 Issue 3. pp. 835-846. DOI: https://doi.org/10.1145/1141911.1141964
Vedaldi, A. An open Implementation of the SIFT detector and descriptor. UCLA CSD Technical Report, 070012, 2007.
Wu, Ch. et al. Multicore Bundle Adjustment. IEEE Computer Vision and Pattern Recognition. 2011, Colorado Springs.
Wu, Ch. SiftGPU Ver. 400. USA, 2012. Available at http://www.cs.unc.edu/~ccwu/siftgpu/
Wu, Ch. VisualSFM Ver. 0.5.22. USA, 2013. Available at http://homes.cs.washington.edu/~ccwu/vsfm/.