Biologically Motivated Novel Localization Paradigm by High-Level Multiple Object Recognition in Panoramic Images
This paper presents the novel paradigm of a global localization method motivated by human visual systems (HVSs). HVSs actively use the information of the object recognition results for self-position localization and for viewing direction. The proposed localization paradigm consisted of three parts:...
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Format: | Article |
Language: | English |
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Wiley
2015-01-01
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Series: | The Scientific World Journal |
Online Access: | http://dx.doi.org/10.1155/2015/465290 |
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author | Sungho Kim Min-Sheob Shim |
author_facet | Sungho Kim Min-Sheob Shim |
author_sort | Sungho Kim |
collection | DOAJ |
description | This paper presents the novel paradigm of a global localization method
motivated by human visual systems (HVSs). HVSs actively use the information
of the object recognition results for self-position localization and for
viewing direction. The proposed localization paradigm consisted of three parts: panoramic image acquisition, multiple object recognition, and grid-based
localization. Multiple object recognition information from panoramic
images is utilized in the localization part. High-level object information
was useful not only for global localization, but also for robot-object interactions.
The metric global localization (position, viewing direction) was
conducted based on the bearing information of recognized objects from just
one panoramic image. The feasibility of the novel localization paradigm
was validated experimentally. |
format | Article |
id | doaj-art-fab1cbb17b134461873790d2d45797a7 |
institution | Kabale University |
issn | 2356-6140 1537-744X |
language | English |
publishDate | 2015-01-01 |
publisher | Wiley |
record_format | Article |
series | The Scientific World Journal |
spelling | doaj-art-fab1cbb17b134461873790d2d45797a72025-02-03T06:08:16ZengWileyThe Scientific World Journal2356-61401537-744X2015-01-01201510.1155/2015/465290465290Biologically Motivated Novel Localization Paradigm by High-Level Multiple Object Recognition in Panoramic ImagesSungho Kim0Min-Sheob Shim1Advanced Visual Intelligence Laboratory, Yeungnam University, 280 Daehak-ro, Gyeongsan, Gyeongbuk 712-749, Republic of KoreaAdvanced Visual Intelligence Laboratory, Yeungnam University, 280 Daehak-ro, Gyeongsan, Gyeongbuk 712-749, Republic of KoreaThis paper presents the novel paradigm of a global localization method motivated by human visual systems (HVSs). HVSs actively use the information of the object recognition results for self-position localization and for viewing direction. The proposed localization paradigm consisted of three parts: panoramic image acquisition, multiple object recognition, and grid-based localization. Multiple object recognition information from panoramic images is utilized in the localization part. High-level object information was useful not only for global localization, but also for robot-object interactions. The metric global localization (position, viewing direction) was conducted based on the bearing information of recognized objects from just one panoramic image. The feasibility of the novel localization paradigm was validated experimentally.http://dx.doi.org/10.1155/2015/465290 |
spellingShingle | Sungho Kim Min-Sheob Shim Biologically Motivated Novel Localization Paradigm by High-Level Multiple Object Recognition in Panoramic Images The Scientific World Journal |
title | Biologically Motivated Novel Localization Paradigm by High-Level Multiple Object Recognition in Panoramic Images |
title_full | Biologically Motivated Novel Localization Paradigm by High-Level Multiple Object Recognition in Panoramic Images |
title_fullStr | Biologically Motivated Novel Localization Paradigm by High-Level Multiple Object Recognition in Panoramic Images |
title_full_unstemmed | Biologically Motivated Novel Localization Paradigm by High-Level Multiple Object Recognition in Panoramic Images |
title_short | Biologically Motivated Novel Localization Paradigm by High-Level Multiple Object Recognition in Panoramic Images |
title_sort | biologically motivated novel localization paradigm by high level multiple object recognition in panoramic images |
url | http://dx.doi.org/10.1155/2015/465290 |
work_keys_str_mv | AT sunghokim biologicallymotivatednovellocalizationparadigmbyhighlevelmultipleobjectrecognitioninpanoramicimages AT minsheobshim biologicallymotivatednovellocalizationparadigmbyhighlevelmultipleobjectrecognitioninpanoramicimages |