This thesis presents a 3D reconstruction software pipeline that is capable of generating
point cloud data from uncalibrated underwater video. This research project was undertaken
as a partnership with 2G Robotics, and the pipeline described in this thesis will become
the 3D reconstruction engine for a software product that can generate photo-realistic 3D
models from underwater video. The pipeline proceeds in three stages: video tracking,
projective reconstruction, and autocalibration.
Video tracking serves two functions: tracking recognizable feature points, as well as selecting well-spaced
keyframes with a wide enough baseline to be used in the reconstruction. Video tracking is accomplished
using Lucas-Kanade optical flow as implemented in the OpenCV toolkit. This simple and
widely used method is well-suited to underwater video, which is taken by carefully piloted
and slow-moving underwater vehicles.
Projective reconstruction is the process of simultaneously calculating the motion of the
cameras and the 3D location of observed points in the scene. This is accomplished using
a geometric three-view technique. Results are presented
showing that the projective reconstruction algorithm detailed here compares favourably to
state-of-the-art methods.
Autocalibration is the process of transforming a projective reconstruction, which is not
suitable for visualization or measurement, into a metric space where it can be used. This
is the most challenging part of the 3D reconstruction pipeline, and this thesis presents a
novel autocalibration algorithm. Results are shown for two existing cost function-based
methods in the literature which failed when applied to underwater video, as well as the
proposed hybrid method. The hybrid method combines the best parts of its two parent
methods, and produces good results on underwater video.
Final results are shown for the 3D reconstruction pipeline operating on short under-
water video sequences to produce visually accurate 3D point clouds of the scene, suitable
for photorealistic rendering. Although further work remains to extend and improve the
pipeline for operation on longer sequences, this thesis presents a proof-of-concept method
for 3D reconstruction from uncalibrated underwater video.
| Identifer | oai:union.ndltd.org:WATERLOO/oai:uwspace.uwaterloo.ca:10012/6242 |
| Date | January 2011 |
| Creators | Cavan, Neil |
| Source Sets | University of Waterloo Electronic Theses Repository |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
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