Advertisement

Earth Science Informatics

, Volume 7, Issue 2, pp 71–81 | Cite as

Terrestrial photogrammetry without ground control points

  • G. Forlani
  • L. Pinto
  • R. Roncella
  • D. Pagliari
Research Article

Abstract

Terrestrial photogrammetry should be the survey technique of choice when updating large scale urban maps and GIS databases, where 3D data and attribute data are required. Its main drawback is the need for Ground Control Points (GCP) to reference the survey. To make image georeferencing easier and to provide control information, the use of a simple system, made of a photogrammetric camera fastened to a GPS antenna, is proposed. A photogrammetric block, composed by at least three images, is taken around the object with the receiver measuring in kinematic mode. Tie points are automatically extracted by Structure from Motion (SfM) algorithms or measured manually; block orientation is performed by GPS assisted Aerial Triangulation. Advantages as well as limitations of the system are discussed, with particular attention to GPS availability or ill-conditioned block configurations. The issue of system calibration (i.e. measurement of eccentricity between camera and antenna) is also addressed. Several test cases are presented, in which absolute accuracies, verified on check points independently surveyed range from 4 to 7 cm.

Keywords

Terrestrial photogrammetry GPS Network RTK Block adjustment Georeferencing 

References

  1. Ackermann F (1984) Utilization of navigation data for aerial triangulation. International Archives of Photogrammetry and Remote Sensing, ISPRS Commission III, Vol. 25, Part A3a, Rio de Janeiro, pp. 1–9.Google Scholar
  2. Agarwal S, Furukawa Y, Snavely N, Simon I, Curless B, Seitz SM, Szeliski R (2011) Building Rome in a day. Communications of the ACM 54(10):105–112CrossRefGoogle Scholar
  3. Bay H, Ess A, Tuytelaars T, Van Gool L (2008) SURF: Speeded up robust features. Computer Vision and Image Understanding (CVIU) 110(3):346–359CrossRefGoogle Scholar
  4. Beis JS, Lowe DG, (1997) Shape indexing using approximate nearest-neighbour search in high-dimensional spaces. In: Proc.of CVPR 1997, pp. 1000–1006.Google Scholar
  5. Biagi et al. (2006) Il Servizio di Posizionamento in Regione Lombardia e la prima sperimentazione sui servizi di rete in tempo reale. Bollettino della SIFET n° 1, 2006Google Scholar
  6. Buckley SJ, Vallet J, Wheeler W, Braathen A (2008) Oblique helicopter-based Laser scanning for digital terrain modeling and visualization of geological outcrops, The Internal Archives of the Photogrammetry, remote sensing and Spatial Information sciences, Beijing, Commission IV/4, pp. 493–498.Google Scholar
  7. Ellum C, El-Sheimy N (2000) The development of a backpack mobile mapping systems, International archives of the Photogrammetry, Remote sensing and spatial information sciences, Vol. XXXIII Part B2, (CD), Amsterdam, The Netherlands, pp. 184–191.Google Scholar
  8. Ellum C, El-Sheimy N (2001) A mobile mapping system for the survey community, Proc. of The 3rd Int. Symp. on Mobile Mapping Technology, Cairo, Egypt, January 3–5, 2001, (CD).Google Scholar
  9. 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 24(3):81–95Google Scholar
  10. Forlani G, Pinto L, (1994) Experiences of combined block adjustment with GPS data. International Archives of Photogrammetry and Remote Sensing, ISPRS Commission III, Vol. 30 Part 3/1, Muenchen, pp. 219–226.Google Scholar
  11. Forlani G, Pinto L (2002) Integrated INS/DGPS systems: Calibration and combined block adjustment, Proceedings, OEEPE Workshop “Integrated Sensor Orientation”, Hannover, Sept. 17–18, 2001, OEEPE Official Publication N°. 43, 2002, pp. 85–96.Google Scholar
  12. 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, Vienna, 3–5 Oct. 2005, Vichman Verlag, Vol I, pp. 265–274Google Scholar
  13. Fraser CS (1997) Digital camera self-calibration. ISPRS Journal of Photogrammetry and Remote Sensing 52:149–159CrossRefGoogle Scholar
  14. Furukawa Y, Ponce J (2010) Accurate, dense, and robust multi-view Stereopsis. IEEE Transactions on PAMI, Vol. 32, Issue 8, August 2010, pp 1362–1376.Google Scholar
  15. Gillet J, McCuiag R, Scherzinger B, Lithopoulos E (2001) Tightly coupled inertial/GPS system for precision forestry surveys under canopy: Test results. First International Precision Forestry Symposium, University of Washington, College of Forest Resources, Seattle, pp 131–138Google Scholar
  16. Harris C, Stephens M (1988) A combined corner and edge detector. Alvey Vision Conference, pp. 147–151Google Scholar
  17. Hartley R, Zisserman A (2000) Multiple view geometry in computer vision. Cambridge University Press, Cambridge, pp 1–496Google Scholar
  18. Heipke C, Jacobsen K, Wegmann H (2002) Analysis of the Results of the OEEPE Test Integrated Sensor Orientation. OEEPE Official Publication, No 43:31–49Google Scholar
  19. Jacobsen K (2000) Potential and limitation of direct sensor orientation, Int. Arch. of Photogrammetry and Remote Sensing, Amsterdam, The Netherlands, Vol. 33, Part B3/1, pp. 429–435Google Scholar
  20. Kraus K (1997) Photogrammetry, vol 2. Dümmler, Bonn, 466 ppGoogle Scholar
  21. Lowe D (2004) Distinctive image feature from scale-invariant keypoints. International Journal of Computer Vision 60(2):91–110Google Scholar
  22. Nister D (2004) An efficient solution to the five-point relative pose problem. IEEE T, Pattern Anal 26(6):756–770CrossRefGoogle Scholar
  23. Roncella R, Re C, Forlani G (2011) Comparison of two structure and motion strategies. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume 38-5/W16, pp. 1–8, CD-ROMGoogle Scholar
  24. Schwarz KP, Fraser CS, Gustafson PC (1984) Aerotriangulation without ground control. International Archives of Photogrammetry and Remote Sensing, ISPRS Commission I, Vol. 25, Part A1, Rio de Janeiro, pp. 237–250.Google Scholar
  25. Vallet J (2001) Design of a helicopter based portable handheld mobile system for avalanche mapping. Proc. of The 3rd Int. Symp. on Mobile Mapping Technology, Cairo, Egypt, January 3–5, 2001, (CD).Google Scholar
  26. Vallet J, Skaloud J, Koelbl O, Merminod B (2000) Development of a Helicopter-based integrated system for avalanche and hazard management. International. Archives of Photogrammetry and Remote Sensing. Vol. XXXIII part B2, (CD), Amsterdam, The Netherlands, pp. 565–572Google Scholar
  27. Van der Vegt HJW (1989) GPS test flight Flevoland. Schriftenreihe des Instituts für Photogrammetrie, Universität Stuttgart, Vol 13, pp. 285–298Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • G. Forlani
    • 1
  • L. Pinto
    • 2
  • R. Roncella
    • 1
  • D. Pagliari
    • 2
  1. 1.Department of Civil EngineeringParma UniversityParmaItaly
  2. 2.D.I.C.A.Politecnico di MilanoMilanItaly

Personalised recommendations