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Video Scene and Event Detection

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Encyclopedia of Database Systems
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Synonyms

Video scene and event extraction

Definition

A video scene, also called a Logical Story Unit [7] or simply a story unit, can be defined as a semantically related consecutive series of image frames that depicts and conveys a high-level concept such as event, topic, object, location, and action, which constitutes a story in a video. Especially, an event can be defined as an incident or situation, which occurs in a particular place during a particular interval of time, for example – homerun in a baseball game, actor’s entrance on stage, car explosion on a highway, etc. Under these definitions, video scene and event detection is to find all video intervals corresponding to a specific event from a given video.

Historical Background

Video scene and event detection has been an active research area in the community of multimedia signal processing and computer vision, and has attracted much interest in many applications such as multimedia information retrieval, video archive indexing...

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Recommended Reading

  1. Adams B., Amir A., Iyengar G., Lin C.-Y., Naphade M., Neti C., and Smith J.R. Semantic indexing of multimedia content using visual, audio and text cues. EURASIP J. Appl. Signal Processing, 2:1–16, 2003.

    MATH  Google Scholar 

  2. Babaguchi N., Kawai Y., and Kitahashi T. Event based indexing of broadcasted sports video by intermodal collaboration. IEEE Trans. Multimedia, 4(1):68–75, 2002.

    Article  Google Scholar 

  3. Babaguchi N. and Nitta N. Intermodal collaboration: a strategy for semantic content analysis for broadcasted sports video. In Proc. Int. Conf. Image Processing, 1:13–16, 2003.

    Google Scholar 

  4. Chua T.-S. and Xu H. Fusion of AV features and external information sources for event detection in team sports video. ACM Trans. Multimedia Comput. Commun. Appl., 2(1):44–67, 2006.

    Article  Google Scholar 

  5. Goh K.-S., Miyahara K., Radhakrishan R., Xiong Z., and Divakaran A. Audio-visual event detection based on mining of semantic audio-visual labels. MERL, TR-2004-008, 2004.

    Google Scholar 

  6. Gong Y. and Xu W. Machine Learning for Multimedia Content Analysis. Springer, Berlin, 2007.

    Google Scholar 

  7. Hanjalic A., Lagendijk R.L., and Biemond J. Automated high-level movie segmentation for advanced video-retrieval systems. IEEE Trans. Circ. Syst. Video Techn., 9(4):580–588, 1999.

    Article  Google Scholar 

  8. Hauptmann A.G. and Smith M.A. Text, speech, and vision for video segmentation: the informedia project. In Proc. AAAI Symp. on Computational Models for Integrating Language and Vision, 1995, pp. 90–95.

    Google Scholar 

  9. Li Y. and Kuo C.-C.J. Video content analysis using multimodal information: for movie content exraction, indexing and representation. Kluwer, Norwell, MA, USA, 2003.

    Google Scholar 

  10. Lienhart R., Pfeiffer S., and Effelsberg W. Video abstracting. Commun. ACM, 40(12):55–62, 1997.

    Article  Google Scholar 

  11. Merlino A., Morey D., and Maybury M. Broadcast news navigation using story segmentation. In Proc. 5th ACM Int. Conf. on Multimedia, 1997, pp. 381–391.

    Google Scholar 

  12. Rui Y., Huang T.S., and Mehrotra S. Constructing table-of-content for videos. ACM Multimed. Syst. J., 7(5):359–368, 1999.

    Article  Google Scholar 

  13. Sundaram H. and Chang S.-F. Computable scenes and structures in films. IEEE Trans. Multimedia, 4(4):482–491, 2002.

    Article  Google Scholar 

  14. The National Institute of Standards and Technology (NIST). TREC video retrieval evaluation. 2001–2007, http://www-nlpir.nist.gov/projects/trecvid/

  15. Xie L., Xu P., Chang S.-F., Divakaran A., and Sun H. Structure analysis of soccer video with domain knowledge and hidden Markov models. Pattern Recogn. Lett., 25(7):767–775, 2004.

    Article  Google Scholar 

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Babaguchi, N., Nitta, N. (2009). Video Scene and Event Detection. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_1022

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