dc.contributor.author | Beall, Chris | |
dc.contributor.author | Lawrence, Brian J. | |
dc.contributor.author | Ila, Viorela | |
dc.contributor.author | Dellaert, Frank | |
dc.date.accessioned | 2011-03-29T18:28:30Z | |
dc.date.available | 2011-03-29T18:28:30Z | |
dc.date.issued | 2010 | |
dc.identifier.citation | Beall, C., Lawrence, B.J., Ila, V., & Dellaert, F. (2010). "3D Reconstruction of Underwater Structures". Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 18-22 October 2010, 4418-4423 | en_US |
dc.identifier.issn | 2153-0858 | |
dc.identifier.uri | http://hdl.handle.net/1853/38324 | |
dc.description | ©2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. | en_US |
dc.description | Presented at the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010), 18-22 October 2010, Taipei, Taiwan. | |
dc.description | DOI: 10.1109/IROS.2010.5649213 | |
dc.description.abstract | Environmental change is a growing international
concern, calling for the regular monitoring, studying and
preserving of detailed information about the evolution of
underwater ecosystems. For example, fragile coral reefs are
exposed to various sources of hazards and potential destruction,
and need close observation. Computer vision offers promising
technologies to build 3D models of an environment from two dimensional
images. The state of the art techniques have
enabled high-quality digital reconstruction of large-scale structures,
e.g., buildings and urban environments, but only sparse
representations or dense reconstruction of small objects have
been obtained from underwater video and still imagery. The
application of standard 3D reconstruction methods to challenging
underwater environments typically produces unsatisfactory
results. Accurate, full camera trajectories are needed to serve as
the basis for dense 3D reconstruction. A highly accurate sparse
3D reconstruction is the ideal foundation on which to base
subsequent dense reconstruction algorithms. In our application
the models are constructed from synchronized high definition
videos collected using a wide baseline stereo rig. The rig can
be hand-held, attached to a boat, or even to an autonomous
underwater vehicle. We solve this problem by employing a
smoothing and mapping toolkit developed in our lab specifically
for this type of application. The result of our technique is
a highly accurate sparse 3D reconstruction of underwater
structures such as corals. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Georgia Institute of Technology | en_US |
dc.subject | Computer vision | en_US |
dc.subject | Images | en_US |
dc.subject | Simultaneous localization and mapping | en_US |
dc.subject | Structure from motion | en_US |
dc.subject | 3D reconstruction | en_US |
dc.subject | Underwater ecosystems | en_US |
dc.title | 3D Reconstruction of Underwater Structures | en_US |
dc.type | Post-print | en_US |
dc.type | Proceedings | |
dc.contributor.corporatename | Georgia Institute of Technology. Center for Robotics and Intelligent Machines | |
dc.contributor.corporatename | Georgia Institute of Technology. College of Computing | |
dc.contributor.corporatename | Institut de Robòtica i Informàtica Industrial | |
dc.publisher.original | Institute of Electrical and Electronics Engineers | |