DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Ro, Yong-Man | - |
dc.contributor.advisor | 노용만 | - |
dc.contributor.author | Min, Hyun-Seok | - |
dc.contributor.author | 민현석 | - |
dc.date.accessioned | 2015-04-23T08:12:46Z | - |
dc.date.available | 2015-04-23T08:12:46Z | - |
dc.date.issued | 2014 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=568619&flag=dissertation | - |
dc.identifier.uri | http://hdl.handle.net/10203/197785 | - |
dc.description | 학위논문(박사) - 한국과학기술원 : 정보통신공학과, 2014.2, [ vi, 69 p. ] | - |
dc.description.abstract | The detection of near-duplicate video clips (NDVCs) is a fundamental requirement of several multi-media applications. Consequently, a strong need exists for techniques that allow identifying NDVCs. Tech-niques for NDVC detection represent a video clip with a unique set of features. Conventional video signatures typically make use of low-level visual features (e.g., color histograms, local interest points). However, low-level visual features are sensitive to transformations of the video content (e.g., blurring and mirroring). Moti-vated by the observation that content transformations tend to preserve the semantic information conveyed by video clips, this dissertation introduces a novel technique for NDVC detection, leveraging model-free semantic concept detection. In particular, we realize model-free semantic concept detection by taking advantage of the collective knowledge in an image folksonomy (i.e., an unstructured collection of user-contributed images and tags), facilitating the use of an unrestricted and dynamic concept vocabulary. Experimental results obtained for the MIRFLICKR-25000 image set (used as a source of collective knowledge) and the TRECVID 2009 video set (used to create query and reference video clips) demonstrate that model-free semantic concept detection can be successfully used for identifying NDVCs. | eng |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | collective knowledge | - |
dc.subject | 복제 비디오 검출 | - |
dc.subject | 비디오 시그너처 | - |
dc.subject | 의미간 거리 | - |
dc.subject | 의미 기반 검출 | - |
dc.subject | 유사 복제 비디오 검출 | - |
dc.subject | image folksonomy | - |
dc.subject | near-duplicate video clip detection | - |
dc.subject | semantic concept detection | - |
dc.subject | semantic distance | - |
dc.subject | semantic video signature | - |
dc.subject | video copy detection | - |
dc.subject | 집단 지능 | - |
dc.subject | 이미지 폭소노미 | - |
dc.title | Semantic concept-based near-duplicate video clip detection | - |
dc.title.alternative | 의미 기반 유사 복제 비디오 검출에 관한 연구 | - |
dc.type | Thesis(Ph.D) | - |
dc.identifier.CNRN | 568619/325007 | - |
dc.description.department | 한국과학기술원 : 정보통신공학과, | - |
dc.identifier.uid | 020085382 | - |
dc.contributor.localauthor | Ro, Yong-Man | - |
dc.contributor.localauthor | 노용만 | - |
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