Probabilistic Approach to Content-Based Indexing and Categorization of Temporally Aggregated Shots in News Videos

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• 关键词：Content ; based video indexing ; Video structures ; News videos ; Temporal aggregation ; News shot categorization ; Category probability ; Temporal relations
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9621
• 期：1
• 页码：741-750
• 全文大小：111 KB
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  3.Choroś, K.: Temporal aggregation of video shots in TV sports news for detection and categorization of player scenes. In: Bădică, C., Nguyen, N.T., Brezovan, M. (eds.) ICCCI 2013. LNCS, vol. 8083, pp. 487–497. Springer, Heidelberg (2013)
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  11.Choroś, K.: Automatic fast detection of anchorperson shots in temporally aggregated TV news videos. In: Nguyen, N.T., Trawiński, B., Kosala, R. (eds.) ACIIDS 2015. LNCS, vol. 9012, pp. 339–348. Springer, Heidelberg (2015)
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  13.Choroś, K.: Video structure analysis and content-based indexing in the automatic video indexer AVI. In: Nguyen, N.T., Zgrzywa, A., Czyżewski, A. (eds.) Advances in Multimedia and Network Information System Technologies. AISC, vol. 80, pp. 79–90. Springer, Heidelberg (2010)CrossRef
  14.Choroś, K.: Automatic categorization of shots in news videos based on the temporal relations. In: Núñez, M., Nguyen, N.T., Camacho, D., Trawiński, B. (eds.) Computational Collective Intelligence. LNCS, vol. 9330, pp. 13–23. Springer, Heidelberg (2015)CrossRef
  15.Choroś, K.: Automatic detection of headlines in temporally aggregated TV sports news videos. In: Proceedings of the 8th International Symposium on Image and Signal Processing and Analysis (ISPA 2013), pp. 147–152. IEEE (2013)
  
• 作者单位：Kazimierz Choroś (17)
  
  17. Faculty of Computer Science and Management, Wrocław University of Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland
  
• 丛书名：Intelligent Information and Database Systems
• ISBN：978-3-662-49381-6
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

The most frequently stored and browsed videos in Web video collections, TV shows archives, documentary video archives, video-on-demand systems, personal video archives, etc. are broadcast news videos and sports news videos. Content-based indexing of news videos is based on the automatic detection of shots, i.e. of the main structural video units. Video shots can be of different categories such as intro and final animation, chart, diagram or table shots, anchor, reporter, statement, or interview shots, and finally the most informative report shots. The content analysis of a video shot is a very time-consuming process using specific strategy adequate for a given shot category. To analyse faster the content of videos it is desirable to reduce the video space analysed in time-consuming content-based indexing by using temporal aggregation. The temporal aggregation results in grouping of shots of the same event or the same category into scenes. Furthermore, the determination on the basis of time relations of the most likely category also reduces the analysis time enabling us to apply the adequate method of analysis as the first. The paper examines the usefulness of the time relations of shots to determine the most likely category of a shot and to optimize the order of applied strategies.