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Multi-camera System Calibration with Built-in Relative Orientation Constraints (Part 1) Theoretical Principle
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 Title & Authors
Multi-camera System Calibration with Built-in Relative Orientation Constraints (Part 1) Theoretical Principle
Lari, Zahra; Habib, Ayman; Mazaheri, Mehdi; Al-Durgham, Kaleel;
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 Abstract
In recent years, multi-camera systems have been recognized as an affordable alternative for the collection of 3D spatial data from physical surfaces. The collected data can be applied for different mapping(e.g., mobile mapping and mapping inaccessible locations)or metrology applications (e.g., industrial, biomedical, and architectural). In order to fully exploit the potential accuracy of these systems and ensure successful manipulation of the involved cameras, a careful system calibration should be performed prior to the data collection procedure. The calibration of a multi-camera system is accomplished when the individual cameras are calibrated and the geometric relationships among the different system components are defined. In this paper, a new single-step approach is introduced for the calibration of a multi-camera system (i.e., individual camera calibration and estimation of the lever-arm and boresight angles among the system components). In this approach, one of the cameras is set as the reference camera and the system mounting parameters are defined relative to that reference camera. The proposed approach is easy to implement and computationally efficient. The major advantage of this method, when compared to available multi-camera system calibration approaches, is the flexibility of being applied for either directly or indirectly geo-referenced multi-camera systems. The feasibility of the proposed approach is verified through experimental results using real data collected by a newly-developed indirectly geo-referenced multi-camera system.
 Keywords
Multi-camera system;Calibration;Mounting parameters;Positioning and orientation system;Indirect georeferencing;
 Language
English
 Cited by
 References
1.
Admas, D. (2007), Commercial marine-based mobile mapping and survey systems, Proceedings of the 5th International Symposium on Mobile Mapping Technology MMT '07, Padua, Italy.

2.
Casella, V., Galetto, R., and Franzini, M. (2006), An Italian project on the evaluation of direct georeferencing in photogrammetry, Proceedings Eurocow 2006

3.
Cramer, M., Stallmann, D., and Haala, N. (1999), Sensor integration and calibration of digital airborne threeline camera systems, Proceedings of the International Workshop on Mobile Mapping Technology, Bangkok, Thailand, pp. 451-458.

4.
Cramer, M. and Stallmann, D. (2002), System calibration for direct georeferencing, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 34, No. 3/A, Proceedings of the ISPRS Commision III Symposium Photogrammetric Computer Vision, pp. 79-84.

5.
Detchev, I., Habib, A., and Chang, Y.-C. (2011), Image matching and surface registration for 3D reconstruction of a scoliotic torso, Geomatica, Vol. 65, pp. 175-187. crossref(new window)

6.
Detchev, I., Habib, A., and El- Badry, M. (2013), Dynamic beam deformation measurements with off-the-shelf digital cameras, Journal of Applied Geodesy, Vol. 7, pp. 147-157.

7.
El-Sheimy, N. (1992), A mobile multi-sensor system for GIS applications in urban centers, International Archives of Photogrammetry and Remote Sensing, Vol. 31, No. B2, pp. 55-100.

8.
El-Sheimy, N. (1996), The Development of VISAT : A Mobile Survey System for GIS Applications, Ph.D. dissertation, Department of Geomatics Engineering, University of Calgary, 198p.

9.
Ellum, C. (2001), The Development of a Backpack Mobile Mapping System, M.Sc. thesis, Department of Geomatics Engineering, University of Calgary, 172p.

10.
Fraser, C.S. (1997), Digital camera self-calibration, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 52, pp. 149-159. crossref(new window)

11.
Fritsch, D., Abdel-Wahab, M., Cefalu, A., and Wenzel, K. (2012), Photogrammetric point cloud collection with multi-camera systems, Progress in Cultural Heritage Preservation, Lecture Notes in Computer Science, Springer Berlin Heidelberg, pp. 11-20.

12.
Granshaw, S.I. (1980), Bundle adjustment methods in engineering photogrammetry, The Photogrammetric Record, Vol. 10, pp. 181-207.

13.
Habib, A., Kersting, A.P., and Bang, K.-I. (2010), Comparative analysis of different approaches for the incorporation of position and orientation information in integrated sensor orientation procedures, Proccedings of Canadian Geomatics Conference 2010 and ISPRS COM I Symposium, Calgary, Canada.

14.
Habib, A., Kersting, A.P., Bang, K.-I., and Rau, J. (2011), A novel single-step procedure for the calibration of the mounting parameters of a multi-camera terrestrial mobile mapping system, Archives of Photogrammetry, Cartography and Remote Sensing, Vol. 22, pp. 173-185.

15.
Haala, N. and Rothermel, M. (2012), Dense multiple stereo matching of highly overlapping UAV imagery, International Archives of Photogrammetry and Remote Sensing and Spatial Information Sciences, Vol. 39, No. B1, pp. 387-392.

16.
Horn, B.K. (1987), Closed-form solution of absolute orientation using unit quaternions, Journal of the Optical Society of America, Vol. 4, pp. 629-642.

17.
King, B. (1992), Optimisation of bundle adjustments for stereo photography, International Archives of Photogrammetry and Remote Sensing, Vol. 29, No. B5, pp. 168-173.

18.
Kobayashi, K. and Mori, C. 1997. Relations between the coefficients in the projective transformation equations and the orientation elements of a photograph, Photogrammetric engineering and remote sensing, Vol. 63, pp. 1121-1127.

19.
Kobayashi, K. and Mori, C. 1997. Relations between the coefficients in the projective transformation equations and the orientation elements of a photograph, Photogrammetric engineering and remote sensing, Vol. 63, pp. 1121-1127.

20.
Lee, C.N., Lee, B.K., and Eo, Y.D. 2008. Experiment on camera platform calibration of a multi-looking camera system using single non-metric camera, Journal of the Korean Society of Surveying, Geodesy, Photgrammetry, and Cartography, Vol. 26, No. 4, pp. 351-357.

21.
Lerma, J.L., Navarro, S., Cabrelles, M., and Seguí, A.E. (2010), Camera calibration with baseline distance constraints, The Photogrammetric Record, Vol. 25, pp. 140-158 crossref(new window)

22.
Malian, A., Azizi, A., and Heuvel, F.A. (2004), Medphos : a New Photogrammetric System for Medical Measurement, Proceedings of Commission V. Presented at the XXth ISPRS Congress, Istanbul, Turkey, pp. 311-316.

23.
Mostafa, M.M.R., Hutton, J., and Lithopoulos, E. (2001), Airborne direct georeferencing of frame imagery: An error budget, Proceedings of the 3rd International Symposium on Mobile Mapping Technology, Cairo, Egypt.

24.
Pinto, L. and Forlani, G. (2002), A single-step calibration procedure for IMU/GPS in aerial photogrammetry, International Archives of Photogrammetry and Remote Sensing, Vol. 34, No. 3, pp. 210-213.

25.
Rau, J.-Y., Habib, A.F., Kersting, A.P., Chiang, K.-W., Bang, K.-I., Tseng, Y.-H., and Li, Y.-H. (2011), Direct sensor orientation of a land-based mobile mapping system, Sensors, Vol. 11, pp. 7243-7261. crossref(new window)

26.
Seedahmed, G.H. and Habib, A.F. (2002), Linear recovery of the exterior orientation parameters in a planar object space, International Archives of Photogrammetry and Remote Sensing, Vol. 34, No. 3, pp. 245-248.

27.
Skaloud, J. (1999), Optimizing Georeferencing of Airborne Survey Systems by INS/DGPS, Ph.D. dissertation, Department of Geomatics Engineering, University of Calgary, 179p.

28.
Shu, F., Zhang, J., and Li, Y. (2009), A multi-camera system for precise pose estimation in industrial applications, Proceedings of the IEEE International Conference on Automation and Logistics, ICAL '09, pp. 206-211.

29.
Smith, M.J., Qtaishat, K.S., Park, D.W.G., and Jamieson, A. (2006), IMU and digital aerial camera misalignment calibration, Proceedings of EuroCow 2006.

30.
Tommaselli, A.M.G., Galo, M., de Moraes, M.V.A., Marcato, J., Caldeira, C.R.T., and Lopes, R.F. (2013), Generating virtual images from oblique frames, Remote Sensing, Vol. 5, pp. 1875-1893. crossref(new window)

31.
Wang, P.C., Tsai, P.C., Chen, Y.C., and Tseng, Y.H. (2012), One-step and two-step calibration of a portable panoramic image mapping system, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 39, No. B1, pp. 173-178.

32.
Yuan, X. (2008), A novel method of systematic error compensation for a position and orientation system, Progress in Natural Science, Vol. 18, pp. 953-963. crossref(new window)