Dynamic template update for visual object tracking시각적 객체 추적을 위한 동적 템플릿 업데이트

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dc.contributor.authorKibum Yun-
dc.date.accessioned2023-06-26T19:33:51Z-
dc.date.available2023-06-26T19:33:51Z-
dc.date.issued2022-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1008358&flag=dissertationen_US
dc.identifier.urihttp://hdl.handle.net/10203/309872-
dc.description학위논문(석사) - 한국과학기술원 : 전기및전자공학부, 2022.8,[iii, 26 p. :]-
dc.description.abstractSiamese-based trackers have recently demonstrated impressive performance and high speed. Despite their great success, conventional siamese trackers are prone to be fooled when facing appearance variations of target objects because they refer to fixed templates captured from first frames to track target objects in the rest of videos. To address this issue, we propose a novel siamese-based tracking framework utilizing a dual template which consists of a static template and a dynamic template. The dynamic template is updated every update interval and allows the tracker to catch appearance variations of the target over time. Furthermore, we introduce a reliability score which prevents incorrect dynamic templates from degrading tracking performance to ensure reliable dynamic template updates. Experimental results show that our method possesses better discriminability and robustness than the baseline, which utilizes a single static template.-
dc.languageeng-
dc.publisher한국과학기술원-
dc.subjectVisual Object Tracking▼aSiamese Network▼aDynamic Template Update-
dc.subject시각적 물체 추적▼a샴 네트워크▼a동적 템플릿 업데이트-
dc.titleDynamic template update for visual object tracking-
dc.title.alternative시각적 객체 추적을 위한 동적 템플릿 업데이트-
dc.typeThesis(Master)-
dc.identifier.CNRN325007-
dc.description.department한국과학기술원 :전기및전자공학부,-
dc.contributor.alternativeauthor윤기범-
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