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DC Field | Value | Language |
---|---|---|
dc.citation.endPage | 243 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 227 | - |
dc.citation.title | MULTIMEDIA TOOLS AND APPLICATIONS | - |
dc.citation.volume | 74 | - |
dc.contributor.author | Jo, Ahra | - |
dc.contributor.author | Jang, Gil-Jin | - |
dc.contributor.author | Han, Bohyung | - |
dc.date.accessioned | 2023-12-22T01:43:29Z | - |
dc.date.available | 2023-12-22T01:43:29Z | - |
dc.date.created | 2015-03-02 | - |
dc.date.issued | 2015-01 | - |
dc.description.abstract | This paper proposes an efficient algorithm for detecting occlusions in a video sequences of ground vehicles using color information. The proposed method uses a rectangular window to track a target vehicle, and the window is horizontally divided into several sub-regions of equal width. Each region is determined to be occluded or not based on the color histogram similarity to the corresponding region of the target. The occlusion detection results are used in likelihood computation of the conventional tracking algorithm based on particle filtering. Experimental results in real scenes show that the proposed method finds the occluded region successfully and improves the performance of the conventional trackers. | - |
dc.identifier.bibliographicCitation | MULTIMEDIA TOOLS AND APPLICATIONS, v.74, no.1, pp.227 - 243 | - |
dc.identifier.doi | 10.1007/s11042-013-1846-5 | - |
dc.identifier.issn | 1380-7501 | - |
dc.identifier.scopusid | 2-s2.0-84921357750 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/10727 | - |
dc.identifier.url | http://link.springer.com/article/10.1007%2Fs11042-013-1846-5 | - |
dc.identifier.wosid | 000348356300015 | - |
dc.language | 영어 | - |
dc.publisher | SPRINGER | - |
dc.title | Occlusion detection using horizontally segmented windows for vehicle tracking | - |
dc.type | Article | - |
dc.description.isOpenAccess | FALSE | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems; Computer Science, Software Engineering; Computer Science, Theory & Methods; Engineering, Electrical & Electronic | - |
dc.relation.journalResearchArea | Computer Science; Engineering | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | Computer vision | - |
dc.subject.keywordAuthor | Histogram similarity | - |
dc.subject.keywordAuthor | Object tracking | - |
dc.subject.keywordAuthor | Occlusion detection | - |
dc.subject.keywordAuthor | Particle filters | - |
dc.subject.keywordPlus | MEAN SHIFT | - |
dc.subject.keywordPlus | VISUAL TRACKING | - |
dc.subject.keywordPlus | OBJECT TRACKING | - |
dc.subject.keywordPlus | MULTIPLE | - |
dc.subject.keywordPlus | KERNEL | - |
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