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Content-based retrieval of Flash™ movies: research issues, generic framework, and future directions

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Abstract

As a prevailing web media format, nowadays Flash™ movies are created, delivered, and viewed by over millions of users in their daily experiences with the Internet. However, issues regarding the indexing and retrieval of Flash movies are unfortunately overlooked by the research community, which severely restrict the utilization of the extremely valuable Flash resource. A close examination reveals that the intrinsic complexity of a Flash movie, including its heterogeneous media components, its dynamic nature, and user interactivity, makes content-based Flash retrieval a host of research issues not thoroughly addressed by the existing techniques. As the first endeavor in this area, we propose a generic framework termed as FLAME (FLash Access and Management Environment) embodying a 3-layer structure that addresses the representation, indexing, and retrieval of Flash movies by mining and understanding of the movie content. An experimental prototype for Flash retrieval is implemented to verify the feasibility and effectiveness of FLAME, and future research directions on Flash management and retrieval are discussed in details.

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References

  1. Adali S, Sapino ML, Subrahmanian VS (2000) An algebra for creating and querying multimedia presentations. ACM Multimedia Syst 8(3):212–230

    Article  Google Scholar 

  2. Al-Khatib W, Ghafoor A (1999) An approach for video meta-data modeling and query processing. In Proc. of ACM Multimedia, pp 215–224

  3. Chan SSM, Li Q (1999) Developing an object-oriented video database system with spatio-temporal reasoning capabilities. In Proc. 18th Int. Conf. on Conceptual Modeling, LNCS 1728, pp 47–61

  4. Chang SK, Shi QY, Yan CY (1987) Iconic indexing by 2-D strings. IEEE Tran Pattern Anal Machine Intell 9(3):413–428

    Article  Google Scholar 

  5. Chang SF, Chen W, Meng HJ, Sundaram H, Zhong D (1997) VideoQ: an automated content based video search system using visual cues. In Proc. ACM Int. Multimedia Conf., pp 313–324

  6. Elmasri R, Navathe B (1994) Fundamentals of database systems (2 Edition). Benjamin/Cummings, Redwood City, CA

    MATH  Google Scholar 

  7. Flash Kit. http://www.flashkit.com/index.shtml

  8. Flickner M, Sawhney H, Niblack W, Ashley J, Huang Q, Dom B, Gorkani M, Hafner J, Lee D, Petkovic D, Steele D, Yanker P (1995) Query by image and video content: the QBIC system. IEEE Comput 28(9):23–32

    Google Scholar 

  9. Foote J (1999) An overview of audio information retrieval. ACM Multimedia Syst 7:2–10

    Article  Google Scholar 

  10. Furht B (1998) Handbook of multimedia computing. CRC, Sep.

  11. Gudivada VN, Raghavan (1995) Design and evaluation of algorithms for image retrieval by spatial similarity. ACM Trans Inf Sys 13(2):115–144

    Article  Google Scholar 

  12. Hauptmann A, Ng TD, Baron R, Lin W, Chen, MY, Derthick M, Christel M, Jin R, Yan R (2002) Video classification and retrieval with the informedia digital video library system. Text Retrieval Conference, Gaithersburg, Maryland, November

  13. Hjelsvold R, Midtstraum R (1994) Modeling and querying video data. In Proc. 20th Int. Conf. Very Large Database, pp 686–694

  14. JavaSWF. http://www.anotherbigidea.com/javaswf/

  15. Lee T, Sheng L, Bozkaya T, Ozsoyoglu G, Ozsoyoglu M (1999) Querying multimedia presentations based on content. IEEE Trans Knowl Data Eng 11(3):361–387

    Article  Google Scholar 

  16. Liu WY, Chen Z, Lin F, Yang R, Li MJ, Zhang HJ (2001) Ubiquitous media agents for managing personal multimedia files. In Proc. ACM Multimedia Conf., pp 519–521

  17. Macromedia, Inc. http://www.macromedia.com

  18. Macromedia Flash Player adoption statistics. http://www.macromedia.com/software/player_census/flashplayer

  19. Macromedia Flash File Format (SDK) http://www.macromedia.com/software/flash/open/licensing/fileformat/

  20. Niblack W, SlideFinder W (1999) A tool for browsing presentation graphics using content-based retrieval. In IEEE Workshop on Content-Based Access of Image and Video Libraries, June 22–22, Fort Collins, Colorado

  21. Ozsoyoglu G, Snodgrass R (1995) Temporal and real-time databases: a survey. IEEE Trans Knowl Data Eng 7(4):513–532

    Article  Google Scholar 

  22. Rui Y, Huang TS, Mehrotra S (1997) Content-based image retrieval with relevance feedback in MARS. In Proc. IEEE Int. Conf. on Image Processing, pp 815–818

  23. Rui Y, Huang TS, Ortega M, Mehrotra S (1998) Relevance feedback: a power tool in interactive content-based image retrieval. IEEE Trans Circuits Syst Video Technol 8(5):644–655

    Article  Google Scholar 

  24. Salton G, McGill MJ (1983) Introduction to modern information retrieval. McGraw-Hill

  25. Samet H (1984) The quadtree and related hierarchical data structures. ACM Comput Surv 16(2):187–260

    Article  MathSciNet  Google Scholar 

  26. Smeulders A et al (2000) Content-based image retrieval at then end of the early years. IEEE Trans Pattern Anal Mach Intell 22(12):1349–1380

    Article  Google Scholar 

  27. Smith JR, Chang SF (1996) VisualSEEk: a fully automated content-based image query system. In Proc. of ACM Multimedia Conf., Boston, MA, pp 87–98

  28. Synchronized Multimedia Integration Language (SMIL). http://www.w3.org/AudioVideo/

  29. Text Retrieval Conference (TREC) Data. http://trec.nist.gov/data.html

  30. Woods S, Yang Q (1995) Program understanding as constraint satisfaction. In Proc. 2nd Working Conf. Reverse Engineering, pp 314–323, Canada

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Authors and Affiliations

  1. Department of Computer Engineering and Information Technology, City University of Hong Kong, Kowloon, HKSAR, People’s Republic of China

    Jun Yang & Qing Li

  2. School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA

    Jun Yang

  3. Department of Computer Science, City University of Hong Kong, Kowloon, HKSAR, People’s Republic of China

    Liu Wenyin

  4. Department of Computer Science, Zhejiang University, Hangzhou, 310027, People’s Republic of China

    Yueting Zhuang

Authors
  1. Jun Yang
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  2. Qing Li
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  3. Liu Wenyin
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  4. Yueting Zhuang
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Corresponding author

Correspondence to Qing Li.

Additional information

The work described in this paper was supported by a grant from CityU (Project No. 7001384); a substantial amount of work by this author was conducted when he was a research assistant at City University of Hong Kong.

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Yang, J., Li, Q., Wenyin, L. et al. Content-based retrieval of Flash™ movies: research issues, generic framework, and future directions. Multimed Tools Appl 34, 1–23 (2007). https://doi.org/10.1007/s11042-006-0058-7

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