Geometric Calibration of Digital Cameras for 3D Cumulus Cloud Measurements

Jiuxiang Hu Division of Computing Studies, Arizona State University, Mesa, Arizona

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Anshuman Razdan Division of Computing Studies, Arizona State University, Mesa, Arizona

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Joseph A. Zehnder Department of Atmospheric Sciences, Creighton University, Omaha, Nebraska

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Abstract

A technique for calibrating digital cameras for stereo photogrammetry of cumulus clouds is presented. It has been applied to characterize the formation of summer thunderstorms observed during the Cumulus Photogrammetric, In Situ, and Doppler Observations (CuPIDO) project. Starting from gross measurements of locations, orientations of cameras, and landmark surveys, accurate locations and orientations of the cameras are obtained by minimizing a geometric error (GE). Once accurate camera parameters are obtained, 3D positions of cloud-feature points are computed by triangulation.

The main contributions of this paper are as follows. First, it is proven that the GE has only one minimum in the neighborhood of the real parameters of a camera. In other words, searching the minimum of the GE enables the authors to find the right camera parameters even if there are significant differences between the initial measurements and their true values. Second, a new coarse-to-fine iterative algorithm is developed that minimizes the GE and finds the camera parameters. Numerical experiments show that the coarse-to-fine algorithm is efficient and effective. Third, a new landmark survey based on a geographic information system (GIS) rather than field measurements is presented. The GIS landmark survey is an effective and efficient way to obtain landmark world coordinates for camera calibrations in these experiments. Validation of this technique is achieved by the data collected by a NASA/Earth Observing System satellite and an instrumented aircraft. This paper builds on previous research and details the calibration and 3D reconstructions.

Corresponding author address: Jiuxiang Hu, Image and 3D Data Exploration and Analysis (I3DEA) Lab, Division of Computing Studies, Arizona State University, Polytech Campus, Mesa, AZ 85212. Email: hu.jiuxiang@asu.edu

Abstract

A technique for calibrating digital cameras for stereo photogrammetry of cumulus clouds is presented. It has been applied to characterize the formation of summer thunderstorms observed during the Cumulus Photogrammetric, In Situ, and Doppler Observations (CuPIDO) project. Starting from gross measurements of locations, orientations of cameras, and landmark surveys, accurate locations and orientations of the cameras are obtained by minimizing a geometric error (GE). Once accurate camera parameters are obtained, 3D positions of cloud-feature points are computed by triangulation.

The main contributions of this paper are as follows. First, it is proven that the GE has only one minimum in the neighborhood of the real parameters of a camera. In other words, searching the minimum of the GE enables the authors to find the right camera parameters even if there are significant differences between the initial measurements and their true values. Second, a new coarse-to-fine iterative algorithm is developed that minimizes the GE and finds the camera parameters. Numerical experiments show that the coarse-to-fine algorithm is efficient and effective. Third, a new landmark survey based on a geographic information system (GIS) rather than field measurements is presented. The GIS landmark survey is an effective and efficient way to obtain landmark world coordinates for camera calibrations in these experiments. Validation of this technique is achieved by the data collected by a NASA/Earth Observing System satellite and an instrumented aircraft. This paper builds on previous research and details the calibration and 3D reconstructions.

Corresponding author address: Jiuxiang Hu, Image and 3D Data Exploration and Analysis (I3DEA) Lab, Division of Computing Studies, Arizona State University, Polytech Campus, Mesa, AZ 85212. Email: hu.jiuxiang@asu.edu

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  • Damiani, R., and Coauthors, 2008: Cumulus Photogrammetric, In Situ and Doppler Observations: The CuPIDO 2006 experiment. Bull. Amer. Meteor. Soc., 89 , 5773.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Diner, J. D., and Coauthors, 1998: Multi-angle Imaging Spectroradiometer (MISR) instrument description and experiment overview. IEEE Trans. Geosci. Remote Sens., 36 , 10721087.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hartley, R., and Zisserman A. , 2003: Multiple View Geometry in Computer Vision. 2nd ed. Cambridge University Press, 672 pp.

  • Holle, R. L., 1982: Photogrammetry of thunderstorms. Thunderstorms: A Social and Technological Documentary, E. Kessler, Ed., University of Oklahoma Press, 77–98.

    • Search Google Scholar
    • Export Citation
  • Mohan, R., Medioni G. , and Nevatia R. , 1989: Stereo error detection correction and evalution. IEEE Trans. Pattern Anal. Mach. Intell., 11 , 113120.

  • Orville, H. D., and Kassander A. R. , 1961: Terrestrial photogrammetry of clouds. J. Meteor., 18 , 682687.

  • Pollefeys, M., Gool L. V. , Vergauwen M. , Verbiest F. , Cornelis K. , Tops J. , and Koch R. , 2004: Visual modeling with a hand-held camera. Int. J. Comput. Vision, 11 , 207232.

    • Search Google Scholar
    • Export Citation
  • Rasmussen, E. N., Davises-Jones R. , and Holle R. L. , 2003: Terrestrial photogrammetry of weather images acquired in uncontrolled circumstances. J. Atmos. Oceanic Technol., 20 , 17901803.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Saunders, P. M., 1963: Simple sky photogrammetry. Weather, 18 , 811.

  • Sourimant, G., Morin L. , and Bouatouch K. , 2007: GPS GIS and video registration for building reconstruction. IEEE Int. Conf. Image Process., 6 , 401404.

    • Search Google Scholar
    • Export Citation
  • Tsai, R. Y., 1987: A versatile camera calibration technique for high-accuracy 3D machine vision meteorology using off-the-shelf TV cameras and lens. IEEE J. Robot. Auto., RA-3 , 323344.

    • Search Google Scholar
    • Export Citation
  • Tsai, R. Y., and Huang T. S. , 1984: Uniqueness and estimation of three-dimensional motion parameters of rigid objects with curved surfaces. IEEE Trans. Pattern Anal. Mach. Intell., 14 , 1327.

    • Search Google Scholar
    • Export Citation
  • van Huffel, S., and Vandewalle J. , 1989: Analysis and properties of the generalized total least squares problem AX ≈ B when some or all columns in A are subject to error. SIAM J. Matrix Anal. Appl., 10 , 294315.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Warner, C., Renick J. , Balshaw M. W. , and Douglas R. H. , 1973: Stereo photogrammetry of cumulonimbus clouds. Quart. J. Roy. Meteor. Soc., 99 , 105115.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weng, J., Cohen P. , and Herniou M. , 1992: Camera calibration with distortion models and accuracy evaluation. IEEE Trans. Pattern Anal. Mach. Intell., 6 , 965980.

    • Search Google Scholar
    • Export Citation
  • Zehnder, J. A., Hu J. , and Razdan A. , 2007: A stereo photogrammetric technique applied to orographic convection. Mon. Wea. Rev., 135 , 22652277.

  • Zhang, Z., 1998: Determining the epipolar geometry and its uncertainty: A review. Int. J. Comput. Vision, 27 , 161198.

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