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Joint 4-D Variational Stereo Reconstruction and Camera Calibration Refinement for Oceanic Sea State Measurements

[+] Author Affiliations
Ping-Chang Shih, Anthony Yezzi, Francesco Fedele

Georgia Institute of Technology, Atlanta, GA

Guillermo Gallego

Universidad Politecnica de Madrid, Madrid, Spain

Paper No. OMAE2014-23653, pp. V01AT01A049; 8 pages
  • ASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering
  • Volume 1A: Offshore Technology
  • San Francisco, California, USA, June 8–13, 2014
  • Conference Sponsors: Ocean, Offshore and Arctic Engineering Division
  • ISBN: 978-0-7918-4537-0
  • Copyright © 2014 by ASME


Validating modern oceanographic theories using models produced through stereo computer vision principles has recently emerged. Space-time (4-D) models of the ocean surface may be generated by stacking a series of 3-D reconstructions independently generated for each time instant or, in a more robust manner, by simultaneously processing several snapshots coherently in a true “4-D reconstruction.” However, the accuracy of these computer-vision-generated models is subject to the estimations of camera parameters, which may be corrupted under the influence of natural factors such as wind and vibrations. Therefore, removing the unpredictable errors of the camera parameters is necessary for an accurate reconstruction. In this paper, we propose a novel algorithm that can jointly perform a 4-D reconstruction as well as correct the camera parameter errors introduced by external factors. The technique is founded upon variational optimization methods to benefit from their numerous advantages: continuity of the estimated surface in space and time, robustness, and accuracy. The performance of the proposed algorithm is tested using synthetic data produced through computer graphics techniques, based on which the errors of the camera parameters arising from natural factors can be simulated.

Copyright © 2014 by ASME



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