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N. E. Cazzaniga; D. Pagliari; L. Pinto (2012)
Publisher: Copernicus Publications
Journal: The International Archives of the Photogrammetry
Languages: English
Types: Article
Subjects: TA1-2040, T, TA1501-1820, Applied optics. Photonics, Engineering (General). Civil engineering (General), Technology
Ground Penetrating Radar (GPR) is an active instrument often used to detect underground utility locations up to a few meters. To perform a three-dimensional reconstruction of position and geometry of the surveyed features, the accuracy of GPR position data has to be in the order of 20-30 cm. This requirement is easily attainable using a GNSS system in open sky conditions, while in urban areas signal leakage is frequent, leading to inadequate position accuracy or even positioning failure. Usually, in those cases, GPS/INS navigation systems are used, but they are quite an expensive solution. To determine the position of the GPR, another strategy could be utilizing a photogrammetric method that uses information extracted from a large scale map, often available for towns. In this paper, the characteristics of this procedure and some possible configurations of cameras are described. Results obtained from preliminary tests are hereby presented and discussed to demonstrate that the proposed methodology could achieve the required precision.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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    • Vehicle Positioning in urban areas using photogrammetry and digital maps. Proceedings of the ENC-GNSS09, Napoli (Italy).
    • Bay H., Ess A., Tuylelaars T., Van Gool., 2008. Speeded Robust Features (SURF). Computer Vision and Image Understanding (110), pp. 346-359.
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    • Bollettino di Geodesia e Scienze Affini, 57(1), pp. 41-60 El-Sheimy, N., Schwarz, K. P., Gravel, M. 1995. Mobile 3-D Positioning Using GPS/INS/Video Cameras, The Mobile Mapping Symposium, Ohio State, USA, pp. 236-249.
    • Fischler, M., Bolles, R.,1981. Random sample consensus: a paradigm for model fitting with application to image analysis and automated cartography. Commun. Assoc. Comp. Mach., Vol 24, pp. 81-95.
    • Forlani, G., Roncella, R., Remondino, F., 2005. Structure and motion reconstruction of short mobile mapping image sequences. Proc. of the 7th Conf. On Optical 3D measurement techniques, Vol I, pp. 265-274, Vienna (A).
    • Hassan, T., Ellum, C., El-Sheimy, N., 2007. Bridging landmobile mapping using photogrammetric adjustments. ISPRS Commision Technique I. 185, pp. 66-72.
    • Roncella, R., Re, C., Forlani, G., 2011a. Comparison of two structure and motion strategies. ISPRS Volume XXXVIII-5/W16.
    • Roncella, R. Re, C., Forlani, G., 2011b. Performance evaluation of a structure and motion strategy in architecture and cultural heritage. ISPRS Volume XXXVIII-5/W16.
    • Roncella, R., Remondino,F., Forlani,G., 2005.
    • Vol.5665, pp. 308-319 Tao, C., Chapman, M. A., El-Sheimy, N., Chaplin, B., 1999.
    • Towards automated processing of mobile mapping image sequences. International Archives of Photogrammetry and Remote Sensing, Vol. 32(2W1).
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