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Underwater Photogrammetry Reconstruction: GPU Texture Generation from Videos Captured via AUV

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Advances in Visual Computing (ISVC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11844))

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Abstract

Photogrammetry is a useful tool for creating computer models of archaeological sites for monitoring and for general public outreach. Modeling archaeological sites found in the marine environment is particularly challenging due to danger to divers, the cost of underwater photography equipment and lighting challenges. The automatic acquisition of video footage of underwater marine archaeology sites using an AUV can be an advantageous alternative, yet also incurs its own obstacles. In this paper we present our system and enhancements for applying a standard photogrammetry reconstruction pipeline to underwater sites using video footage captured from an AUV. Our primary contribution is a GPU driven algorithm for texture construction to reduce blur in the final model. We demonstrate the results of our system on a well known wreck site in Malta.

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Acknowledgements

We would like to acknowledge the entire 2018 ICEX team. This material is based upon work supported by the National Science Foundation under Grant No. 1460153.

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Authors and Affiliations

  1. Computer Science Department, California Polytechnic State University, San Luis Obispo, CA, USA

    Kolton Yager & Zoë J. Wood

  2. Engineering Department, Harvey Mudd College, Claremont, CA, USA

    Christopher Clark

  3. Department of Classics and Archeology, University of Malta, Msida, Malta

    Timmy Gambin

Authors
  1. Kolton Yager
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  2. Christopher Clark
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  3. Timmy Gambin
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  4. Zoë J. Wood
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Corresponding author

Correspondence to Kolton Yager .

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Editors and Affiliations

  1. University of Nevada, Reno, NV, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. University of Nevada, Reno, NV, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Daniela Ushizima

  6. Latent AI, Palo Alto, CA, USA

    Sek Chai

  7. Texas A&M University, College Station, TX, USA

    Shinjiro Sueda

  8. Louisiana State University, Baton Rouge, LA, USA

    Xin Lin

  9. University of North Carolina at Charlotte, Charlotte, NC, USA

    Aidong Lu

  10. École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Daniel Thalmann

  11. Notre Dame University, Notre Dame, IN, USA

    Chaoli Wang

  12. Bosch Research North America, Palo Alto, CA, USA

    Panpan Xu

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Yager, K., Clark, C., Gambin, T., Wood, Z.J. (2019). Underwater Photogrammetry Reconstruction: GPU Texture Generation from Videos Captured via AUV. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2019. Lecture Notes in Computer Science(), vol 11844. Springer, Cham. https://doi.org/10.1007/978-3-030-33720-9_10

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  • DOI: https://doi.org/10.1007/978-3-030-33720-9_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33719-3

  • Online ISBN: 978-3-030-33720-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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