Structured Light Methods: From Land to Undersea

  • Author / Creator
  • Extracting 3D geometry of an object from 2D images has been a popular topic in computer vision for decades. Many methods have been proposed to solve this problem with high accuracy and structured light methods are one of the most commonly used. Despite their high accuracy, there are limitations for existing methods. First, most existing methods can either be applied to obtain dense correspondences but limited to static scenes, or be applied to dynamic scenes but limited to sparse correspondences. Second, existing methods cannot be applied to scenes with global illuminations such as inter-reflection and projector defocus. Last but not least, existing structured light methods are rarely applied to underwater applications due to the difficulties of underwater camera calibration. Motivated by the above limitations, a new structured light method is presented to establish dense correspondences for dynamic scenes. Many simulated and real datasets are used to test the robustness of this method. Moreover, another novel structured light method is presented in this thesis to account for global illuminations such as inter-reflection, subsurface scattering and severe projector defocus. The experimental results demonstrate that the proposed method consistently outperforms two of the state-of-the-art methods. To address the limitation in underwater applications, two new underwater camera calibration methods are presented by using the physically correct refraction model. All the experimental results of applying these two methods are evaluated against the ground truth, and the simulated experiments are compared to the methods that produces the best results. The comparison demonstrates that our results are promising. The most significant advantage of these two methods is that no calibration object is required, which can be very difficult to access when the cameras are deployed undersea. Finally, a multi-camera multi-projector system is designed and developed to monitor the undersea habitat. Since 2014, the system has been deployed along the coast of B.C., collecting data that can be shared with researchers from around the world.

  • Subjects / Keywords
  • Graduation date
  • Type of Item
  • Degree
    Doctor of Philosophy
  • DOI
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
  • Institution
    University of Alberta
  • Degree level
  • Department
    • Department of Computing Science
  • Supervisor / co-supervisor and their department(s)
    • Herb Yang (Computing Science)
  • Examining committee members and their departments
    • Hong Zhang (Computing Science)
    • Martin Jagersand (Computing Science)
    • Aksel Hallin (Physics)