Title:
Horizon Line Estimation In Glacial Environments Using Multiple Visual Cues

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dc.contributor.author Williams, Stephen en_US
dc.contributor.author Howard, Ayanna M. en_US
dc.contributor.corporatename Georgia Institute of Technology. Human-Automation Systems Lab en_US
dc.contributor.corporatename Georgia Institute of Technology. School of Electrical and Computer Engineering en_US
dc.contributor.corporatename Georgia Institute of Technology. Center for Robotics and Intelligent Machines en_US
dc.date.accessioned 2011-04-19T20:19:54Z
dc.date.available 2011-04-19T20:19:54Z
dc.date.issued 2011-05
dc.description Presented at the IEEE International Conference on Robotics and Automation (ICRA), Shanghai, China, 9-13 May 2011. en_US
dc.description ©2011 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 DOI: 10.1109/ICRA.2011.5980006 en_US
dc.description.abstract While the arctic possesses significant information of scientific value, surprisingly little work has focused on developing robotic systems to collect this data. For arctic robotic data collection to be a viable solution, a method for navigating in the arctic, and thus of assessing glacial terrain, must be developed. Segmenting the ground plane from the rest of the image is one common aspect of a visual hazard detection system. However, the properties of glacial images, namely low contrast, overcast sky, and cloud, mountain, and snow sharing common colors, pose difficulties for most visual algorithms. A horizon line detection scheme is presented which uses multiple visual cues to rank candidate horizon segments, then constructs a horizon line consistent with those cues. Weak cues serve to reinforce a selected path, while strong cues have the ability to redirect it. Further, the system infers the horizon location in areas that are visually ambiguous. The performance of the proposed system has been tested on multiple data sets collected on two different glaciers in Alaska, and compares favorably, both in terms of time and classification performance, to representative segmentation algorithms from several different classes. en_US
dc.identifier.citation S. Williams, A. Howard, "Horizon Line Estimation In Glacial Environments Using Multiple Visual Cues,” IEEE International Conference on Robotics and Automation (ICRA), Shanghai, China, May 2011, 5887-5892. en_US
dc.identifier.doi 10.1109/ICRA.2011.5980006
dc.identifier.isbn 978-1-61284-386-5
dc.identifier.issn 1050-4729
dc.identifier.uri http://hdl.handle.net/1853/38614
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.publisher.original Institute of Electrical and Electronics Engineers en_US
dc.subject Robotics en_US
dc.subject Glacial environments en_US
dc.title Horizon Line Estimation In Glacial Environments Using Multiple Visual Cues en_US
dc.type Text
dc.type.genre Proceedings
dc.type.genre Post-print
dspace.entity.type Publication
local.contributor.author Howard, Ayanna M.
local.contributor.corporatename School of Civil and Environmental Engineering
local.contributor.corporatename Institute for Robotics and Intelligent Machines (IRIM)
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relation.isOrgUnitOfPublication 88639fad-d3ae-4867-9e7a-7c9e6d2ecc7c
relation.isOrgUnitOfPublication 66259949-abfd-45c2-9dcc-5a6f2c013bcf
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