(A) lecture video segmentation approach in dynamic lecturing environment동적인 강의 환경에서 촬영된 강의 비디오 세그먼테이션을 위한 연구

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One of the fundamental steps for video processing is to decompose a video into meaningful segments. In previous methods, reliable result for the videos recorded under non-stationary environment could not be produced. Moreover, backward-walk slide transition that similar slides are repeated also cannot be detected. We propose a lecture video segmentation method which is available for various type videos and consider the lecturer behavior by using SIFT, adaptive threshold and graph based detection model. The way to know whether slide to slide transition happens or not is made up two main steps. First is similarity computation for which the slide region is detected then similarity between slides is computed by using SIFT. In second step, the graph based transition detection model will be constructed based on the similarity. At that time, threshold is adjusted adaptively according to characteristic of relevant cacheable segment. The slide transition point can be gotten from graph-based transition detection model and adaptive threshold. The experiments performed on various video types show the effectiveness of ours.
Advisors
Kim, Myoung Horesearcher김명호researcher
Description
한국과학기술원 :전산학과,
Publisher
한국과학기술원
Issue Date
2013
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 전산학과, 2013.8 ,[vii, 35 p. :]

Keywords

Lecture video; video segmentation; video processing; 강의 비디오; 세그먼테이션; 비디오 처리

URI
http://hdl.handle.net/10203/221855
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=657355&flag=dissertation
Appears in Collection
CS-Theses_Master(석사논문)
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