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Video Databases

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Encyclopedia of Multimedia
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Definition

Video database research falls into the following categories: video data models, video extraction, video query language, and video index structures.

Introduction

The past decade has seen explosive growth in the ability of individuals to create and/or capture digital video, leading slowly to large scale personal and corporate digital video banks. Over the last 8–10 years, there has been a tremendous amount of work on creating video databases. Video database research falls primarily into the following categories:

  1. 1.

    Video data models. What kind of data about a video should we store?

  2. 2.

    Video extraction. How should this data be automatically extracted from a video?

  3. 3.

    Video query language. How should we query this data?

  4. 4.

    Video index structures. How should we index this data for faster retrieval?

We discuss multiple potential answers to these four important topics.

Video Data Models

Throughout this paper, we will assume that a video υ is divided up into a sequence b...

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References

  1. G. Boccignone, A. Chianese, V. Moscato, and A. Picariello, “Foveated Shot Detection for Video Segmentation,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 15, No. 3, 2005, pp. 365–377.

    Google Scholar 

  2. K. Koijima, M. Hironaga, S. Nagae, and Y. Kawamoto, “Human Motion Analysis Using the Rhythm – A Reproducing Method of Human Motion,” Journal of Geometry and Graphics, Vol. 5, No. 1, 2001, pp. 45–49.

    Google Scholar 

  3. L. Bretzner, I. Laptev, and T. Lindeberg, “Hand Gesture Recognition Using Multi-Scale Colour Features, Hierarchical and Particle Filtering,” Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition (FGR'02), IEEE Computer Society, 2002, pp. 1–6.

    Google Scholar 

  4. A.F. Bobick and J.W. Davis, “The Recognition of Human Movement Using Temporal Templates,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23, No. 3, 2001 pp. 257–267.

    Google Scholar 

  5. S. Adali, K.S. Candan, S.-S. Chen, K. Erol, and V.S. Subrahmanian, “AVIS: Advanced Video Information Systems,” ACM Multimedia Systems Journal, Vol. 4, 1996, pp. 172–186.

    Google Scholar 

  6. E. Hwang and V.S. Subrahmanian, “Querying Video Libraries,” Journal of Visual Communication and Image Representation, Vol. 7, No. 1, 1996, pp. 44–60.

    Google Scholar 

  7. H. Martin and R. Lozano, “Dynamic Generation of Video Abstracts Using an Object Oriented Video DBMS,” Networking and Information Systems Journal, Vol. 3, No. 1, 2000, pp. 53–75.

    Google Scholar 

  8. M.R. Lyu, E. Yau, and S. Sze, “A Multilingual, Multimodal Digital Video Library System,” JCDL'02: Proceedings of the Second ACM/IEEE-CS Joint Conference on Digital Libraries, 2002, pp. 145–153.

    Google Scholar 

  9. T. Evgeniou, M. Pontil, C. Papageorgiou, and T. Poggio, “Image Representations and Feature Selection for Multimedia Database Search,” IEEE Transactions on Knowledge and Data Engineering, Vol. 15, No. 4, 2003, pp. 911–920.

    Google Scholar 

  10. M. Betke and N. Makris, “Fast Object Recognition in Noisy Images Using Simulated Annealing,” Proceedings of the Fifth International Conference Computer Vision, 1995, pp. 523–530.

    Google Scholar 

  11. A. Yuille, P. Hallinan, and D. Cohen, “Feature Extraction from Faces Using Deformable Templates,” International Journal on Computer Vision, Vol. 8, No. 2, 1992, pp. 99–111.

    Google Scholar 

  12. B. Moghaddam and A. Pentland, “Probabilistic Visual Learning for Object Detection,” Technical Report 326, Mitmedia, 1995.

    Google Scholar 

  13. M. Osadchy and D. Keren, “A Rejection-Based Method for Event Detection in Video,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 14, No. 4, 2004, pp. 534–541.

    Google Scholar 

  14. H. Sidenbladh, M.J. Black, and D.J. Fleet, “Stochastic Tracking of 3D Human Figures Using 2D Image Motion,” Proceedings of the European Conference on Computer Vision, 2000, pp.702–718.

    Google Scholar 

  15. M.E. Leventon and W.T. Freeman, “Bayesian Estimation of 3-D Human Motion from Image Sequences,” Mitsubishi Electric Research Lab, Vol. TR-98-06, 1998.

    Google Scholar 

  16. M.J. Black, D.J. Fleet, and Y. Yaccob, “Robustly Estimative Changes in Image Appearance,” Computer Vision and Image Understanding, Vol. 78, 2000, pp. 8–31.

    Google Scholar 

  17. A.F. Bobick and J.W. Davids, “The Recognition of Human Movement Using Temporal Templates,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23, 2001, pp. 257–267.

    Google Scholar 

  18. M.R. Lyu, J. Song, and M. Cai, “A Comprehensive Method for Multilingual Video Text Detection, Localization, and Extraction,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 15, No. 2, 2005, pp. 243–255.

    Google Scholar 

  19. A. Chianese, R. Miscioscia, V. Moscato, S. Parlato, and A. Picariello, “A Fuzzy Approach to Video Scenes Detection and its Application for Soccer Matches,” IEEE International Conference on Intelligent Systems Design and Applications, 2004.

    Google Scholar 

  20. M. Fayzullin, V.S. Subrahmanian, M. Albanese, and A. Picariello. “The Priority Curve Algorithm for Video Summarization,” Proceedings of ACM MMDB 2004, pp. 28–35.

    Google Scholar 

  21. A. Picariello, M.L. Sapino, and V.S. Subrahmanian. “Algebraic Video Environment,” in B. Furht and O. Marques (Eds.) “Handbook of Video Data Bases,” CRC, 2003, pp. 457–482.

    Google Scholar 

  22. P. Ciaccia and M. Patella, “Searching in Metric Spaces with User-Defined and Approximate Distances,” ACM Transactions on Database Systems, Vol. 27, No. 4, 2002, pp. 398–437.

    Google Scholar 

  23. V.S. Subrahmanian, “Principles of Multimedia Database Systems,” Morgan Kaufmann, Los Altos, CA, 1998.

    Google Scholar 

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© 2008 Springer-Verlag

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Cesarano, C., Fayzullin, M., Picariello, A., Subrahmanian, V.S. (2008). Video Databases. In: Furht, B. (eds) Encyclopedia of Multimedia. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-78414-4_243

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