Stereovision in underwater environments

Stereoscopic vision is the modern field of using multiple cameras to extract three dimensional information about a scene. This technology is used in a wide variety of applications from motion capture used in the movie industry to the industrial monitoring and validation of production lines. This technology however has seen limited use in the challenging environment of underwater photography. This thesis attempts to implement and adapt this technology for use in the Marine Institute flume tank. The flume tank is used for scientific modeling and validation of fishing gear and other objects in ocean environments. This works focuses on the challenges involved in doing this, as well as experimental validation of modern camera calibration and triangulation and adding several novel improvements on these processes. -- This works shows that a modern system using a properly calibrated system functions faster, more accurately and more precisely than any human driven monitoring system. The testing of the various modern calibration techniques reveals several weaknesses when exposed to the challenging underwater environment. The comparison of several methods for stereo location showed the accuracy of these methods is greatly reduced in challenging environments. Both these results open the way for several novel improvements on the methods which increase accuracy and improve performance over the original methods.

[1]  Kenneth Levenberg A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .

[2]  Janne Heikkilä,et al.  Geometric Camera Calibration Using Circular Control Points , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Richard Szeliski,et al.  A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms , 2001, International Journal of Computer Vision.

[4]  Roger Y. Tsai,et al.  A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses , 1987, IEEE J. Robotics Autom..

[5]  Jean-Yves Bouguet,et al.  Camera calibration toolbox for matlab , 2001 .

[6]  Stephen J. Maybank,et al.  On plane-based camera calibration: A general algorithm, singularities, applications , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[7]  S. Bougnoux,et al.  From projective to Euclidean space under any practical situation, a criticism of self-calibration , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[8]  Jean-Thierry Lapresté,et al.  Dry camera calibration for underwater applications , 2003, Machine Vision and Applications.

[9]  W. Faig CALIBRATION OF CLOSE-RANGE PHOTOGRAMMETRIC SYSTEMS: MATHEMATICAL FORMULATION , 1975 .

[10]  Zhengyou Zhang,et al.  A Flexible New Technique for Camera Calibration , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Alexandru Tupan,et al.  Triangulation , 1997, Comput. Vis. Image Underst..

[12]  Roch M. Comeau,et al.  Incorporation of stereoscopic video into an image-guided neurosurgery environment , 1995, Proceedings of 17th International Conference of the Engineering in Medicine and Biology Society.

[13]  Darius Burschka,et al.  Advances in Computational Stereo , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Carlo Tomasi Camera Calibration , 2002 .

[15]  Charles Hansen,et al.  Rectification of images for binocular and trinocular stereovision , 1988, [1988 Proceedings] 9th International Conference on Pattern Recognition.

[16]  David W. Jacobs,et al.  Linear fitting with missing data: applications to structure-from-motion and to characterizing intensity images , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[17]  Andrea Torsello,et al.  Robust Camera Calibration using Inaccurate Targets , 2010, BMVC.

[18]  George Legge,et al.  Designing and Testing New Fishing Gears: The Value of a Flume Tank , 2006 .

[19]  Feng Zhu,et al.  Design of a novel stereo vision navigation system for mobile robots , 2005, 2005 IEEE International Conference on Robotics and Biomimetics - ROBIO.

[20]  Nicholas Krouglicof,et al.  An Efficient Camera Calibration Technique Offering Robustness and Accuracy Over a Wide Range of Lens Distortion , 2012, IEEE Transactions on Image Processing.