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External Vehicle Positioning System Using Multiple Fish-Eye Surveillance Cameras for Indoor Parking Lots

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dc.contributor.authorKim, Sung-Tae-
dc.contributor.authorFan, Ming-
dc.contributor.authorJung, Seung-Won-
dc.contributor.authorKo, Sung-Jea-
dc.date.accessioned2022-02-14T00:41:07Z-
dc.date.available2022-02-14T00:41:07Z-
dc.date.created2021-12-23-
dc.date.issued2021-12-
dc.identifier.issn1932-8184-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/135683-
dc.description.abstractThe autonomous positioning of a vehicle predominantly relies on the global positioning system (GPS). However, in indoor environments, such as tunnels and indoor parking lots, the accuracy of GPS-based positioning can be significantly reduced due to weak GPS signals. To this end, we develop an accurate indoor vehicle positioning system using multiple fish-eye surveillance cameras. Our system first extracts vehicle segments from the top-view image of each fish-eye camera. These segments are then integrated into a common undistorted coordinate system. The center of the vehicle is finally determined using our simple but effective box fitting method. Moreover, a 1/18 scale indoor parking lot is designed to evaluate the performance of the proposed system. Throughout our experiments, we obtained average positioning errors of 30 or 24 cm in the regions covered by a single camera or multiple cameras, respectively.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.subjectWIDE-ANGLE-
dc.titleExternal Vehicle Positioning System Using Multiple Fish-Eye Surveillance Cameras for Indoor Parking Lots-
dc.typeArticle-
dc.contributor.affiliatedAuthorKo, Sung-Jea-
dc.identifier.doi10.1109/JSYST.2020.3019296-
dc.identifier.scopusid2-s2.0-85121731912-
dc.identifier.wosid000728931100045-
dc.identifier.bibliographicCitationIEEE SYSTEMS JOURNAL, v.15, no.4, pp.5107 - 5118-
dc.relation.isPartOfIEEE SYSTEMS JOURNAL-
dc.citation.titleIEEE SYSTEMS JOURNAL-
dc.citation.volume15-
dc.citation.number4-
dc.citation.startPage5107-
dc.citation.endPage5118-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaOperations Research & Management Science-
dc.relation.journalResearchAreaTelecommunications-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryOperations Research & Management Science-
dc.relation.journalWebOfScienceCategoryTelecommunications-
dc.subject.keywordPlusWIDE-ANGLE-
dc.subject.keywordAuthorCalibration-
dc.subject.keywordAuthorCameras-
dc.subject.keywordAuthorDistortion-
dc.subject.keywordAuthorEstimation-
dc.subject.keywordAuthorFish-eye camera-
dc.subject.keywordAuthorGlobal Positioning System-
dc.subject.keywordAuthorImage segmentation-
dc.subject.keywordAuthorSurveillance-
dc.subject.keywordAuthorimage segmentation-
dc.subject.keywordAuthorindoor navigation-
dc.subject.keywordAuthorsurveillance system-
dc.subject.keywordAuthorvehicle positioning-
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