3D reconstruction of underwater scene for marine bioprospecting using remotely operated underwater vehicle (ROV)
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Marine bioprospecting is the procedure of identifying the characteristics of marine organisms to develop them into commercial products. This paper proposes a 3D reconstruction algorithm to facilitate 3D visualization of underwater scene for the marine bioprospecting using remotely operated underwater vehicle (ROV). It allows to provide an operator with intuitive user interface and accordingly contribute to enhance the operability of the ROV in the bioprospecting operation. The reconstruction algorithm transforms 2D pixel coordinates of the sonar image into the corresponding 3D spatial coordinates of the scene surface by restoring the surface elevation missing in the sonar image. First, the algorithm segments the objects and shadows in the image by classifying the pixels based on the intensity value of the seafloor. Second, it computes the surface elevation on the object pixels based on their intensity values. Third, the elevation correction factor, which is derived by the ratio between height of the object and the length of the shadow, is multiplied to the surface elevation value. Finally, the 3D coordinates of the scene surfaces are reconstructed using the coordinate transformation from the image plane to the seafloor with the restored surface elevation values. The experimental results show the algorithm successfully reconstructs the surface of the reference object within an error range less than 10 % of the object dimension, and practical applicability to the marine bioprospecting operation.
KeywordsMarine bioprospecting Multi-beam imaging sonar Remotely operated underwater vehicle Underwater scene reconstruction
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- D. K. Leary, Bioprospecting and the genetic resources of hydrothermal vents on the high seas: what is the existing legal position, where are we heading and what are our options?, Journal of International and Comparative Environmental Law, 1 (2) (2004) 137–141.Google Scholar
- R. J. Smolowitz, S. H. Patel, H. L. Haas and S. A. Miller, Using a remotely operated vehicle (ROV) to observe loggerhead sea turtle (Caretta caretta) behavior on foraging grounds off the mid–Atlantic United States, Journal of Experimental Marine Biology and Ecology, 471 (2015) 84–91.CrossRefGoogle Scholar
- C. Katlein, M. Nicolaus, M. Hoppmann, F. Wenzhofer and B. Rabe, Advancing interdisciplinary sea ice research with a new under–ice remotely operated vehicle and autonomous observatories, Proc. of Cordon Conference on Polar Marine Science, Ventura, CA, USA (2017).Google Scholar
- T. Parenteau, P. Espinasse, A. Benbia and B. Ngim, Subsea mining field development concept using a subsea crushing and feeding unit, Proc. of Offshore Technology Conference, Huston, Texas, USA (2013) OTC–23953–MS.Google Scholar
- C. Beall, B. J. Lawrence, V. Ila and F. Dellaert, 3D reconstruction of underwater structures, Proc. of International Conference on Intelligent Robots and Systems (IROS), Taipei, Taiwan (2010) 4418–4423.Google Scholar
- V. Brandou, A. G. Allais, M. Perrier, E. Malis, P. Rives, J. Sarrazin and P. M. Sarradin, 3D reconstruction of natural underwater scenes using the stereovision system IRIS, Proc. of OCEANS’07–Europe, Aberdeen, UK (2007) 1–6.Google Scholar
- O. Pizarro, R. Eustice and H. Singh, Large area 3D recon–structions from underwater surveys, Proc. of OCEANS'04, Kobe, Japan (2004) 678–687.Google Scholar
- M. M. Campos and G. O. Codina, Underwater laser–based structured light system for one–shot 3D reconstruction, Proc. of IEEE SENSORS, Valencia, Spain (2014) 1138–1141.Google Scholar
- M. D. Aykin and S. Negahdaripour, Forward–look 2D sonar image formation and 3D reconstruction, Proc. of 2013 Oceans–San Diego, San Diego, CA, USA (2013) 1–10.Google Scholar
- J. B. Hsieh, J. I. Olsonbaker and W. L. Fox, A screening application for image data collected by an acoustic lens sonar, Tech report, DTIC Document (2005).Google Scholar
- W. S. Burdic, Underwater acoustic system analysis, Second Ed., Prentice Hall, New Jersey, USA (1991).Google Scholar