Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/10261/3991
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dc.creatorRamisa, Arnau-
dc.creatorTapus, Adriana-
dc.creatorLopez de Mantaras, Ramon-
dc.creatorToledo, Ricardo-
dc.date2008-05-05T10:18:46Z-
dc.date2008-05-05T10:18:46Z-
dc.date2008-05-
dc.date.accessioned2017-01-31T01:09:45Z-
dc.date.available2017-01-31T01:09:45Z-
dc.identifier978-1-4244-1646-2-
dc.identifier1050-4729-
dc.identifierhttp://hdl.handle.net/10261/3991-
dc.identifier10.1109/ROBOT.2008.4543262-
dc.identifier.urihttp://dspace.mediu.edu.my:8181/xmlui/handle/10261/3991-
dc.descriptionIEEE International Conference on Robotics and Automation (ICRA 2008, Pasadena, California, May 19-23, 2008), pp. 538-543.-
dc.descriptionThis paper presents a vision-based approach for mobile robot localization. The environmental model is topological. The new approach uses a constellation of different types of affine covariant regions to characterize a place. This type of representation permits a reliable and distinctive environment modeling. The performance of the proposed approach is evaluated using a database of panoramic images from different rooms. Additionally, we compare different combinations of complementary feature region detectors to find the one that achieves the best results. Our experimental results show promising results for this new localization method. Additionally, similarly to what happens with single detectors, different combinations exhibit different strengths and weaknesses depending on the situation, suggesting that a context-aware method to combine the different detectors would improve the localization results.-
dc.descriptionThis work was partially supported by USC Women in Science and Engineering (WiSE), the FI grant from the Generalitat de Catalunya, the European Social Fund, and the MID-CBR project grant TIN2006-15140-C03-01 and FEDER funds and the grant 2005-SGR-00093.-
dc.format391461 bytes-
dc.formatapplication/pdf-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers-
dc.relationhttp://dx.doi.org/10.1109/ROBOT.2008.4543262-
dc.rightsopenAccess-
dc.subjectArtificial Intelligence-
dc.subjectMobile Robot-
dc.subjectAffine Regions Detectors-
dc.subjectHarris Affine-
dc.subjectHessian Affine-
dc.subjectMSER-
dc.subjectSIFT-
dc.subjectGLOH-
dc.subjectTopological Localization-
dc.titleMobile Robot Localization using Panoramic Vision and Combinations of Feature Region Detectors-
dc.typeComunicación de congreso-
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