Unsupervised video-shot segmentation and model-free, anchorperson detection for news video story parsing
Publication in refereed journal

香港中文大學研究人員

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摘要News story parsing is an important and challenging task in a news video library system. In this paper, we address two important components in a news video story parsing system: shot boundary detection and anchorperson detection. First, an unsupervised fuzzy c-means algorithm is used to detect video-shot boundaries in order to segment a news video into video shots. Then, a graph-theoretical cluster analysis algorithm is implemented to classify the video shots into anchorperson shots and news footage shots. Because of its unsupervised nature, the algorithms require little human intervention. The efficacy of the proposed method is extensively tested on more than 5 h of news programs.
著者Gao XB, Tang X
期刊名稱IEEE Transactions on Circuits and Systems for Video Technology
出版年份2002
月份9
日期1
卷號12
期次9
出版社IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
頁次765 - 776
國際標準期刊號1051-8215
電子國際標準期刊號1558-2205
語言英式英語
關鍵詞anchorperson detection; cluster analysis; fuzzy clustering; graphtheoretical; video library
Web of Science 學科類別Engineering; Engineering, Electrical & Electronic; ENGINEERING, ELECTRICAL & ELECTRONIC

上次更新時間 2020-22-09 於 01:56