Abstract
We introduce a unified framework for video data mining consisting of a comprehensive video description schema and an intuitive browsing, manipulation and database navigation tool; “VideoViews”. The proposed description schema is based on the structure and the semantics of the video data and incorporates scene, camera, object, track and behavior information pertaining to a large class of video data. The database tool is designed to exploit both the hierarchical structure of video data, the clips, shots or scenes, as well as the semantic structure, such as scene geometry, camera parameters, objects and the object behaviors. VideoViews provides means for intuitive representation and navigation, interactive manipulation, ability to annotate and correlate the data in the video database, while also supporting conventional database queries. This hierarchically and semantically structured browsing tool enables users to freely navigate to perform top-down and bottom-up analysis of the video database to visualize the information and data from a number of perspectives. The VideoViews description schema and the navigation tool are designed and developed as part of a video analysis and content extraction framework devised under U.S. Government ARDA /VACE (Video Analysis and Content Extraction) project.
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
Rui, Y., Huang, T.: Unified Framework for Video Browsing and Retrieval. In: Handbook of Image & Video Processing, pp. 705–715. Academic Press, London (2000)
Idris, F., Panchanathan, S.: Review of Image and Video Indexing Techniques. Jour. of Vis.Comm. And Image Repr. 8(2), 146–166 (1997)
Flickner, M., et al.: Query by Image and Video Content: The QBIC System. Computer 28(9), 23–32 (1995)
Niblack, W., Barber, R., Equitz, W., Glasman, M., Petkovic, D., Yanker, P., Faloutsos, C., Taubin, G.: The QBIC Project: Querying Images by Content Using Color Texture and Shape. Storage Ret. Image Video Databases (1908), 173–187 (1993)
Bach, J.R., Fuller, C., Gupta, A.: The VIRAGE Image Search Engine: An open Framework for Image Management. In: Proc. SPIE 1996, Storage and Retrieval for Still Image and Video Dbase IV, pp. 170–179 (1996)
Wolf, W.: Key Frame Selection by Motion Anlaysis. In: Proceedings of the IEEE International Conference on Acoustic, Speech, and Signal Processing. IEEE, New York (1996)
Zang, H., Low, C.Y., Smoliar, S.W., Zhong, D.: Video parsing, retrieval and browsing: An Integrated And Content-Based Solution. In: Proceedings of the ACM Conference on MultiMedia. ACM, New York (1995)
Zhuang, Y., Rui, Y., Huang, T.S., Mehrotta, S.: Adaptive Key Frame Extraction Using Unsupervised Clustering. In: Proceedings of the IEEE International Conference on Image Processing. IEEE, New York (1988)
Ferman, A.M., Gunsel, B., Tekalp, A.M.: Object-Based Indexing of MPEG-4 Compressed Video. In: Proc. VCIP 1997, vol. SPIE-3024, San Jose CA, pp. 953–963 (1997)
Fan, J., Ji, Y., Wu, L.: Automatic Moving Object Extraction Toward Content-Based Video Representation and Indexing. Journal of Visual Communications and Image Representation 12(3), 217–239 (2001)
Guler, S., Rizkalla, M., Vetter, M.: An Object Behavior And Event Based Index/Browse/Retrieve Framework And Tool For Video Data. In: Proc. 1st Europian Workshop on Content Based Multimedia Indexing, Toulouse France (1999)
Oh, J., Thenneru, M., Jiang, N.: Hierarchical Video Indexing Based on Changes on Camera and Object Motions. In: Proc. of The Eighteenth Annual ACM Symposium on Applied Computing (SAC 2003), Melbourne, Florida (March 2003)
Pan, J.Y., Faloutsos, C.: GeoPlot: Spatial Data Mining on Video Libraries. In: Proceedings of the Eleventh International Conference on Information and Knowledge Management (CIKM 2002), Mclean, Virginia (November 2002)
Guler, S.: Scene and Content Analysis From Multiple Video Streams. In: Proc. 30th AIPR, Washington D.C. (2001)
SMPTE 336M, Television – Data Encoding Protocol Using Key-Length_Value
Liang, W.H.: Mapping KLV Packets into Synchronous MPEG-2 Program Streams. In: Proc. 36th SMPTE Advanced Motion Imaging Conference, Dallas, TX (2002), 36-13-TX.pdf
Zhu, X., Fan, J., Aref, W., Elmagarmid, A.: ClassMiner: Mining medical video content structure and events towards efficient access and scalable skimming. In: Proceedings of the SIGMOD Workshop on Data Mining and Knowledge Discovery, Madison, WI (June 2002)
Giarratano, J.: CLIP’s User’s Guide. Artificial Intelligence Section. Johnson Space Center, NASA (June 1988)
Hauptmann, A., Ng, T.D., Baron, R., Lin, W., Chen, M., Derthick, M., Christel, M., Jin, R., Yan, R.: Video Classification and Retrieval with the Informedia Digital Video Library. In: Text Retrieval Conference (TREC 2002), Gaithersburg, MD (November 2002)
Oh, J., Bandi, B.: Multimedia Data Mining Framework for Raw Video Sequences. In: Proc. of ACM Third International Workshop on Multimedia Data Mining (MDM/ KDD2002), Edmonton, Alberta, Canada (July 2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Guler, S., Pushee, I. (2003). Videoviews: A Content Based Video Description Schema and Database Navigation Tool. In: Zaïane, O.R., Simoff, S.J., Djeraba, C. (eds) Mining Multimedia and Complex Data. PAKDD 2002. Lecture Notes in Computer Science(), vol 2797. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39666-6_9
Download citation
DOI: https://doi.org/10.1007/978-3-540-39666-6_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20305-6
Online ISBN: 978-3-540-39666-6
eBook Packages: Springer Book Archive