Abstract
Similarly to text, video is hierarchically structured. The analogies of text and video structures are discussed. Then the juxtaposition is presented of two indexing processes, i.e. of text and video indexing based on the content analysis of their structure units. Several frameworks of automatic detection and categorisation of video shots and scenes reporting the sport events in a given discipline in TV sports news have already been proposed. It has been observed that many sport videos such as archery, diving, soccer, and tennis have repetitive structure patterns. In the tests performed using the Automatic Video Indexer AVI shots and then scenes have been detected in tested TV news videos. Experimental results show good performance of the scheme of video scene detection of a given sport discipline in TV sports news. The Automatic Video Indexer is a research project investigating tools and techniques of automatic video indexing for retrieval systems.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Lew, M.S., Sebe, N., Djeraba, C., Jain, R.: Content-based multimedia information retrieval: State of the art and challenges. ACM Transactions on Multimedia Computing, Communications, and Applications, 1–19 (2006)
Kang, Y.-L., Lim, J.-H., Kankanhalli, M.S., Xu, C., Tian, Q.: Goal detection in soccer video using audio/visual. In: Proceedings of the ICIP, pp. 1629–1632 (2004)
Yang, Y., Lin, S., Zhang, Y., Tang, S.: A statistical framework for replay detection in soccer video. In: IEEE International Symposium on Circuits and Systems ISCAS 2008, pp. 3538–3541 (2008)
Bertini, M., Del Bimbo, A., Nunziati, W.: Automatic annotation of sport video content. In: Lazo, M., Sanfeliu, A. (eds.) CIARP 2005. LNCS, vol. 3773, pp. 1066–1078. Springer, Heidelberg (2005)
Lien, C.-C., Chiang, C.-L., Lee, C.-H.: Scene-based event detection for baseball videos. Journal of Visual Communication and Image Representation, 1–14 (2007)
Delakis, M., Gravier, G., Gros, P.: Audiovisual integration with segment models for tennis video parsing. Computer Vision and Image Understanding, 142–154 (2008)
Yang, Y., Lin, S., Zhang, Y., Tang, S.: Statistical Framework for Shot Segmentation and Classification in Sports Video. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds.) ACCV 2007, Part II. LNCS, vol. 4844, pp. 106–115. Springer, Heidelberg (2007)
Ariki, Y., Sugiyama, Y.: Classification of TV sports news by DCT features using multiple subspace method. In: Proceedings of Fourteenth International Conference on Pattern Recognition, vol. 2, pp. 1488–1491 (1998)
Messer, K., Christmas, W., Kittler, J.: Automatic sports classification. In: Proceedings of the 16th International Conference on Pattern Recognition, pp. 1005–1008 (2002)
Vakkalanka, S., Mohan, C.K., Kumaraswamy, R., Yegnanarayana, B.: Combining multiple evidence for video classification. In: Proceedings of the International Conference on Intelligent Sensing and Information Processing, pp. 187–192 (2005)
Ling-Yu, D., Min, X., Qi, T., Chang-Sheng, X., Jin, J.S.: A unified framework for semantic shot classification in sports video. IEEE Transactions on Multimedia, 1066–1083 (2005)
Karpenko, A., Aarabi, P.: Tiny videos: a large dataset for image and video frame categorization. In: Proceedings of the 11th IEEE International Symposium on Multimedia ISM 2009, pp. 281–289 (2009)
Wengang, C., Xu, D.: A novel approach of generating video scene structure. In: TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region, vol. 1, pp. 350–353 (2003)
Choroś, K.: Video shot selection and content-based scene detection for automatic classification of TV sports news. In: Internet – Technical Development and Applications, Book Series: Advances in Soft Computing, vol. 64, pp. 73–80. Publisher Springer, Heidelberg (2009)
Liu, C., Huang, Q., Jiang, S., Zhang, W.: Extracting story units in sports video based on unsupervised video scene clustering. In: IEEE International Conference on Multimedia and Expo, pp. 1605–1608 (2006)
Zhang, Y.J., Lu, H.B.: A hierarchical organization scheme for video data. Pattern Recognition 35, 2381–2387 (2002)
Choroś, K.: Digital video segmentation techniques for indexing and retrieval on the Web. In: Advanced Problems of Internet Technologies. Academy of Business, Dąbrowa Górnicza, pp. 7–21 (2008)
Choroś, K., Gonet, M.: Effectiveness of video segmentation techniques for different categories of videos. In: New Trends in Multimedia and Network Information Systems, pp. 34–45. IOS Press, Amsterdam (2008)
Choroś, K., Pawlaczyk, P.: Content-based scene detection and analysis method for automatic classification of TV sports news. In: Szczuka, M. (ed.) RSCTC 2010. LNCS (LNAI), vol. 6086, pp. 120–129. Springer, Heidelberg (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Choroś, K. (2010). 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. Advances in Intelligent and Soft Computing, vol 80. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14989-4_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-14989-4_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14988-7
Online ISBN: 978-3-642-14989-4
eBook Packages: EngineeringEngineering (R0)