Title:
Bayesian Surprise and Landmark Detection
Bayesian Surprise and Landmark Detection
dc.contributor.author | Ranganathan, Ananth | |
dc.contributor.author | Dellaert, Frank | |
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 | Honda Research Institute USA, Inc. | |
dc.date.accessioned | 2011-04-01T19:50:56Z | |
dc.date.available | 2011-04-01T19:50:56Z | |
dc.date.issued | 2009-05 | |
dc.description | ©2009 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 2009 IEEE International Conference on Robotics and Automation (ICRA), 12-17 May 2009, Kobe, Japan. | |
dc.description | DOI: 10.1109/ROBOT.2009.5152376 | |
dc.description.abstract | Automatic detection of landmarks, usually special places in the environment such as gateways, for topological mapping has proven to be a difficult task. We present the use of Bayesian surprise, introduced in computer vision, for landmark detection. Further, we provide a novel hierarchical, graphical model for the appearance of a place and use this model to perform surprise-based landmark detection. Our scheme is agnostic to the sensor type, and we demonstrate this by implementing a simple laser model for computing surprise. We evaluate our landmark detector using appearance and laser measurements in the context of a topological mapping algorithm, thus demonstrating the practical applicability of the detector. | en_US |
dc.identifier.citation | Ranganathan, A., & Dellaert, F. (2009). “Bayesian Surprise and Landmark Detection". Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2009), 12-17 May 2009, 2017-2023. | en_US |
dc.identifier.issn | 1050-4729 | |
dc.identifier.uri | http://hdl.handle.net/1853/38367 | |
dc.language.iso | en_US | en_US |
dc.publisher | Georgia Institute of Technology | en_US |
dc.publisher.original | Institute of Electrical and Electronics Engineers | |
dc.subject | Bayesian surprise | en_US |
dc.subject | Computer vision | en_US |
dc.subject | Landmark detection | en_US |
dc.subject | Topological mapping | en_US |
dc.title | Bayesian Surprise and Landmark Detection | en_US |
dc.type | Text | |
dc.type.genre | Post-print | |
dc.type.genre | Proceedings | |
dspace.entity.type | Publication | |
local.contributor.author | Dellaert, Frank | |
local.contributor.corporatename | Institute for Robotics and Intelligent Machines (IRIM) | |
local.contributor.corporatename | College of Computing | |
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