A New Shape Feature for Vehicle Classification in Thermal Video Sequences

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dc.contributor.authorYang, Dong Wonko
dc.contributor.authorPark, Hyun Wookko
dc.date.accessioned2016-11-09T06:33:22Z-
dc.date.available2016-11-09T06:33:22Z-
dc.date.created2016-10-27-
dc.date.created2016-10-27-
dc.date.issued2016-07-
dc.identifier.citationIEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, v.26, no.7, pp.1363 - 1375-
dc.identifier.issn1051-8215-
dc.identifier.urihttp://hdl.handle.net/10203/213903-
dc.description.abstractSince thermal images represent only the temperature difference between objects and background and they have more blurred edges than color images, the segmented images from them have noisy object boundaries. Therefore, the well-known features developed for color images may not work well with thermal images. To overcome these limitations of thermal images, we propose a novel feature extraction method based on the target trait context (TTC). A robust keypoint detector is also proposed by analyzing the included angle moments of the object boundary points. At each keypoint, we define the boundary shape context and the normalized intensity context, which contain shape information and thermal distribution, respectively, of the object. These two contexts are combined to form a new feature set, the TTC. To validate our proposed feature extraction method, the keypoint repeatability test and the classification performance test were performed and compared with those from the previous methods. The experiment results show that the proposed feature works well for thermal video sequences and outperforms the previous methods in classification performance-
dc.languageEnglish-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.subjectOBJECT RECOGNITION-
dc.subjectIMAGE FEATURES-
dc.subjectRANDOM FORESTS-
dc.subjectDESCRIPTORS-
dc.subjectGRAPHS-
dc.titleA New Shape Feature for Vehicle Classification in Thermal Video Sequences-
dc.typeArticle-
dc.identifier.wosid000384075100013-
dc.identifier.scopusid2-s2.0-84979010959-
dc.type.rimsART-
dc.citation.volume26-
dc.citation.issue7-
dc.citation.beginningpage1363-
dc.citation.endingpage1375-
dc.citation.publicationnameIEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY-
dc.identifier.doi10.1109/TCSVT.2015.2452780-
dc.contributor.localauthorPark, Hyun Wook-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorAutomatic target recognition-
dc.subject.keywordAuthorincluded angle moment-
dc.subject.keywordAuthorthermal vehicle signature-
dc.subject.keywordAuthorvehicle target classification-
dc.subject.keywordPlusOBJECT RECOGNITION-
dc.subject.keywordPlusIMAGE FEATURES-
dc.subject.keywordPlusRANDOM FORESTS-
dc.subject.keywordPlusDESCRIPTORS-
dc.subject.keywordPlusGRAPHS-
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