Video-Based Dynamic Stagger Measurement of Railway Overhead Power Lines Using Rotation-Invariant Feature Matching
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cho, Chul Jin | - |
dc.contributor.author | Ko, Hanseok | - |
dc.date.accessioned | 2021-09-04T15:54:27Z | - |
dc.date.available | 2021-09-04T15:54:27Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2015-06 | - |
dc.identifier.issn | 1524-9050 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/93490 | - |
dc.description.abstract | In this paper we propose an effective method of assessing the reliability of railway overhead power lines by measuring the dynamic stagger of contact wires based on a video monitoring technique. Previously developed video monitoring methods may produce severe errors when applied to tilting trains due to changes in position and orientation of the pantograph. In particular, we propose to employ feature-based image matching techniques that are invariant to rotation and robust to changes in camera viewpoint. A pantograph tilting model is first developed from the video data acquired from an actual train based on the motion dynamics of the stagger behavior on moving train platform. We then evaluate the proposed method by comparing it with the conventional template matching in terms of tracking error. The experimental results confirm that the proposed method shows superior performance in all train traveling sequences, particularly over the pantograph tilting train motion segment. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.subject | FEATURE-EXTRACTION | - |
dc.subject | RECOGNITION | - |
dc.subject | PREDICTION | - |
dc.title | Video-Based Dynamic Stagger Measurement of Railway Overhead Power Lines Using Rotation-Invariant Feature Matching | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Ko, Hanseok | - |
dc.identifier.doi | 10.1109/TITS.2014.2361647 | - |
dc.identifier.scopusid | 2-s2.0-84930958938 | - |
dc.identifier.wosid | 000359252700019 | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, v.16, no.3, pp.1294 - 1304 | - |
dc.relation.isPartOf | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS | - |
dc.citation.title | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS | - |
dc.citation.volume | 16 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 1294 | - |
dc.citation.endPage | 1304 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Transportation | - |
dc.relation.journalWebOfScienceCategory | Engineering, Civil | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Transportation Science & Technology | - |
dc.subject.keywordPlus | FEATURE-EXTRACTION | - |
dc.subject.keywordPlus | RECOGNITION | - |
dc.subject.keywordPlus | PREDICTION | - |
dc.subject.keywordAuthor | Affine moment invariant (AMI) | - |
dc.subject.keywordAuthor | feature extraction | - |
dc.subject.keywordAuthor | scale-invariant feature transform (SIFT) | - |
dc.subject.keywordAuthor | tilting train | - |
dc.subject.keywordAuthor | video-based measurement | - |
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