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Applications of Anisotropic Procrustes Analysis

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Advanced Procrustes Analysis Models in Photogrammetric Computer Vision

Part of the book series: CISM International Centre for Mechanical Sciences ((CISM,volume 590))

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Abstract

As extensively shown in the previous chapters, Procrustes Analysis allows to easily perform transformations among corresponding point coordinates belonging to a generic k-dimensional space and it is therefore suited to solve problems encountered in geodesy, photogrammetric computer vision, and laser scanning.

Co-authored with Valeria Garro, University of Verona (Italy) and Francesco Malapelle, University of Udine (Italy).

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Notes

  1. 1.

    The depth of a point is its distance from the focal plane of the camera.

  2. 2.

    http://cvlab.epfl.ch/~strecha/multiview/denseMVS.html.

  3. 3.

    Exterior orientation requires \(m=3\), but a larger set can be used to improve speed.

  4. 4.

    The C++ code is available on the Web as part of the Theia library (Sweeney 2015).

  5. 5.

    In these experiments on simulated data, measures are in arbitrary “units.”

  6. 6.

    Code available from http://samantha.3dflow.net.

  7. 7.

    Code available from http://vision.ucla.edu/vlg/.

  8. 8.

    Courtesy of N. Haala.

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Authors and Affiliations

  1. University of Udine, Udine, Italy

    Fabio Crosilla, Alberto Beinat, Eleonora Maset & Domenico Visintini

  2. University of Udine, Udine, Italy

    Andrea Fusiello

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  1. Fabio Crosilla
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  2. Alberto Beinat
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Correspondence to Fabio Crosilla .

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Crosilla, F., Beinat, A., Fusiello, A., Maset, E., Visintini, D. (2019). Applications of Anisotropic Procrustes Analysis. In: Advanced Procrustes Analysis Models in Photogrammetric Computer Vision. CISM International Centre for Mechanical Sciences, vol 590. Springer, Cham. https://doi.org/10.1007/978-3-030-11760-3_8

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