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dc.contributor.authorUllah, M. M.
dc.contributor.authorPronobis, A.
dc.contributor.authorCaputo, B.
dc.contributor.authorLuo, J.
dc.contributor.authorJensfelt, Patric
dc.contributor.authorChristensen, Henrik I.
dc.date.accessioned2011-03-14T20:13:09Z
dc.date.available2011-03-14T20:13:09Z
dc.date.issued2008-05
dc.identifier.citationUllah, M. M., Pronobis, A., Caputo, B., Luo, J., Jensfelt, P., and Christensen, H. I. Towards robust place recognition for robot localization. In 2008 IEEE Intl. Conf. on Robotics and Automation (Pasadena, CA, May 2008), pp. 530-537.en_US
dc.identifier.isbn9781424416479
dc.identifier.urihttp://hdl.handle.net/1853/37396
dc.description(c) 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.descriptionPresented at the 2008 IEEE International Conference on Robotics and Automation; Pasadena, CA, USA; May 19-23, 2008.
dc.descriptionDigital Object Identifier: 10.1109/ROBOT.2008.4543261
dc.description.abstractLocalization and context interpretation are two key competences for mobile robot systems. Visual place recognition, as opposed to purely geometrical models, holds promise of higher flexibility and association of semantics to the model. Ideally, a place recognition algorithm should be robust to dynamic changes and it should perform consistently when recognizing a room (for instance a corridor) in different geographical locations. Also, it should be able to categorize places, a crucial capability for transfer of knowledge and continuous learning. In order to test the suitability of visual recognition algorithms for these tasks, this paper presents a new database, acquired in three different labs across Europe. It contains image sequences of several rooms under dynamic changes, acquired at the same time with a perspective and omnidirectional camera, mounted on a socket. We assess this new database with an appearance-based algorithm that combines local features with support vector machines through an ad-hoc kernel. Results show the effectiveness of the approach and the value of the database.en_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectMobile robotsen_US
dc.subjectImage recognitionen_US
dc.subjectAppearance-based algorithmen_US
dc.titleTowards robust place recognition for robot localizationen_US
dc.typeArticleen_US
dc.contributor.corporatenameGeorgia Institute of Technology. College of Computing
dc.contributor.corporatenameIDIAP Research Institute
dc.contributor.corporatenameGeorgia Institute of Technology. Center for Robotics and Intelligent Machines
dc.contributor.corporatenameKungl. Tekniska Högskolan. Centrum för Autonoma System
dc.publisher.originalInstitute of Electrical and Electronics Engineers


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