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Video Content Structure

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Encyclopedia of Database Systems
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Synonyms

Video structuring; Video structure analysis

Definition

Mining video content structure is an elementary step of video content analysis. Direct access to a video without indexing is usually not an easy task, due to its length and unstructured format. On the other hand, analogous to text documents that can be decomposed into chapters, paragraphs, sentences and words, videos can be segmented into units like scenes, shots, and keyframes. The analysis of video content structure can be viewed as the process of hierarchically decomposing videos into units and building their relationships. Through such a process, a table-of-content can be constructed for each video, which facilitates the access and manipulations of the video data. For example, the keyframes extracted from the video can be used as its entries for indexing and browsing.

Historical Background

More and more videodata has become available to ordinary users due to the advances in storage devices, networks and compression...

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  1. Chua T.-S., Chang S.-F., Chaisorn L., and Hsu W. Story boundary detection in large broadcast news video archives - techniques, experiences and trends. In Proc. 12th ACM Int. Conf. on Multimedia, 2004.

    Google Scholar 

  2. Ebadollahi S., Xie L., Chang S.-F., and Smith J.R. Visual event detection using multi-dimensional concept dynamics. In Proc. IEEE Int. Conf. on Multimedia and Expo, 2006.

    Google Scholar 

  3. Gu Z., Mei T., Hua X.-S., Wu X., and Li S. EMS: Energy minimization based video scene segmentation. In Proc. IEEE Int. Conf. on Multimedia and Expo, 2007.

    Google Scholar 

  4. Hanjalic A. and Zhang H.-J. An integrated scheme for automated video abstraction based on unsupervised cluster-validaty analysis. IEEE Trans. Circ. Syst. Video Tech., 9(8):1280–1289, 1999.

    Article  Google Scholar 

  5. Kang H.-W. and Hua X.-S. To learn representativeness of video frames. In Proc. 13th ACM Int. Conf. on Multimedia, 2005.

    Google Scholar 

  6. Kim J.-G., Chang H.S., Kim J., and Kim H.M. Efficient camera motion characterization for MPEG video indexing. In Proc. IEEE Int. Conf. on Multimedia and Expo, 2000.

    Google Scholar 

  7. Ma Y.F., Lu L., Zhang H.-J., and Li M. A user attention model for video summarization. In Proc. 10th ACM Int. Conf. on Multimedia, 2002.

    Google Scholar 

  8. Rasheed Z. and Shah M. Detection and representation of scenes in videos. IEEE Trans. Multimed., 7(6):1097–1105, 2005.

    Article  Google Scholar 

  9. Rasheed Z. and Shah M. Scene detection in holleywood movies and tv shows. In Proc. Int. Conf. on Computer Vision and Pattern Recognition, 2005.

    Google Scholar 

  10. Rui Y., Huang T.S., and Mehrotra S. Constructing table-of-content for video. Multimed. Syst., 7:359–368, 1999.

    Article  Google Scholar 

  11. Tang Y.-P. and Lu H. Model-based clustering and analysis of video scenes. In Proc. Int. Conf. Image Processing, 2002.

    Google Scholar 

  12. Yeung M., Yeo B., and Liu B. Segmentation of videos by clustering and graph analysis. Comput. Vis. Image Understand., 71(1):94–109, 1998.

    Article  Google Scholar 

  13. Yuan J., Wang H., Xiao L., Zheng W., Li J., Lin F., and Zhang B. A formal study of shot boundary detection. IEEE Trans. Circ. Syst. Video Tech., 17:168–186, 2007.

    Article  Google Scholar 

  14. Zhang H.-J., Kankanhalli A., and Smoliar S.W. Automatic paritioning of full-motion video. Multimed. Syst., 1:10–28, 1993.

    Article  Google Scholar 

  15. Zhang H.-J., Tan S.Y., and Smoliar S.W. Automatic parsing and indexing of news video. Multimed. Syst., 2(6):256–265, 1995.

    Article  Google Scholar 

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Hua, XS., Wang, M. (2009). Video Content Structure. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_1020

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