DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yang, Dong Won | ko |
dc.contributor.author | Park, Hyun Wook | ko |
dc.date.accessioned | 2016-11-09T06:33:22Z | - |
dc.date.available | 2016-11-09T06:33:22Z | - |
dc.date.created | 2016-10-27 | - |
dc.date.created | 2016-10-27 | - |
dc.date.issued | 2016-07 | - |
dc.identifier.citation | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, v.26, no.7, pp.1363 - 1375 | - |
dc.identifier.issn | 1051-8215 | - |
dc.identifier.uri | http://hdl.handle.net/10203/213903 | - |
dc.description.abstract | Since 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.language | English | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.subject | OBJECT RECOGNITION | - |
dc.subject | IMAGE FEATURES | - |
dc.subject | RANDOM FORESTS | - |
dc.subject | DESCRIPTORS | - |
dc.subject | GRAPHS | - |
dc.title | A New Shape Feature for Vehicle Classification in Thermal Video Sequences | - |
dc.type | Article | - |
dc.identifier.wosid | 000384075100013 | - |
dc.identifier.scopusid | 2-s2.0-84979010959 | - |
dc.type.rims | ART | - |
dc.citation.volume | 26 | - |
dc.citation.issue | 7 | - |
dc.citation.beginningpage | 1363 | - |
dc.citation.endingpage | 1375 | - |
dc.citation.publicationname | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY | - |
dc.identifier.doi | 10.1109/TCSVT.2015.2452780 | - |
dc.contributor.localauthor | Park, Hyun Wook | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Automatic target recognition | - |
dc.subject.keywordAuthor | included angle moment | - |
dc.subject.keywordAuthor | thermal vehicle signature | - |
dc.subject.keywordAuthor | vehicle target classification | - |
dc.subject.keywordPlus | OBJECT RECOGNITION | - |
dc.subject.keywordPlus | IMAGE FEATURES | - |
dc.subject.keywordPlus | RANDOM FORESTS | - |
dc.subject.keywordPlus | DESCRIPTORS | - |
dc.subject.keywordPlus | GRAPHS | - |
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