Skip to main content

Real-Time Adaptive Shot Change Detection Model

  • Conference paper
Signal Processing and Multimedia (MulGraB 2010, SIP 2010)

Abstract

Shot change detection is the main technique in the video segmentation which is required real-time processing and automatical processing in hardware. In this paper, we propose the SCD model for real-time shot change detection in such as PMPs and cellular phones. The real-time SCD model determines shot change detection by comparing the feature value of current frame and a mean feature value on variable reference block. Proposed method can be used independently from the feature value of frame, can set automatic threshold using a mean feature value on variable reference block. We obtained better detection ratio than the conventional methods maximally by precision 0.146, recall 0.083, F1 0.089 in the experiment with the same test sequence. Therefore, our proposing algorithm will be helpful in searching video data on portable media player such as PMPs and cellular phones.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Cotsaces, C., Nikolaidis, N., Pitas, I.: Video Shot Detection and Condensed Representation. IEEE Signal Processing Magazine 23, 28–37 (2006)

    Article  Google Scholar 

  2. Smoliar, S.W., Zhang, H.J.: Content-Based Video Indexing and Retrieval. IEEE Multimedia 1(2), 62–72 (2006)

    Article  Google Scholar 

  3. Yu, J., Srinath, M.D.: An dfficient method for scene cut detection. Pattern Recognition Letters 22, 1379–1391 (2001)

    Article  MATH  Google Scholar 

  4. Kim, J.R., Suh, S.J., Sull, S.H.: Fast scene change detection for personal video recorder. IEEE Transaction on Consumer Electronics 49, 683–688 (2003)

    Article  Google Scholar 

  5. Zhang, H.J., Kankamhalli, A., Smoliar, S.W.: Automatic partitioning of full-motion video. In: ACM Multimedia Systems, New York (1993)

    Google Scholar 

  6. Hampapur, A., Jain, R., Weymouth, T.: Digital Video Segmentation. In: Proc. ACM Multimedia 1994, pp. 357–364 (1994)

    Google Scholar 

  7. Shahraray, B.: Scene Change Detection and Content-Based Sampling of Video Sequences. In: Proc. in Digital Video Compression: Algorithms and Technologies, vol. SPIE-2419, pp. 2–13 (1995)

    Google Scholar 

  8. Xiong, W., Lee, J.C.M., Shen, D.G.: Net Comparison: An Adaptive and Effective Method for Scene Change Detection. In: SPIE (1995)

    Google Scholar 

  9. Lee, J.C.M., Li, Q., Xiong, W.: Automaeiv and Dynamic Video Manipulation. Research and Development in Information Retrieval (1998)

    Google Scholar 

  10. Tonomura, Y.: Video handing based on structured information for hypermedia system. In: Proc. ACM International Conference Multimedia Information Systems, pp. 333–344 (1991)

    Google Scholar 

  11. Nagasaka, A., Tanaka, Y.: Automatic Video Indexing and Full Video Search For Object Appearances. In: Proceedings of the IFIP TC2/WG 2.6 Second Working Conference on Visual Database Systems II, pp. 113–127 (1991)

    Google Scholar 

  12. Ueda, H., Miyatake, T., Yoshizawa, S.: ImPACT: An Interactive Natural-motion-picture Dedicated Multimedia Authoring System. In: Proceedings of CHI, pp. 343–350 (1991)

    Google Scholar 

  13. Gargi, U., Kasturi, R., Antani, S.: Evaluation of video sequence indexing and hierarchical video indexing. In: Proc. SPIE Conf. Storage and Retrieval in Image and Video Databases, pp. 1522–1530 (1995)

    Google Scholar 

  14. Shin, S.Y., Sheng, G.R., Park, K.H.: A Scene Change Detection Scheme Using Local x^2-Test on Telematics. In: International Conference on Hybrid Information Technology, vol. 1, pp. 588–592 (2006)

    Google Scholar 

  15. Meng, J., Juan, Y., Chang, S.F.: Scene change detection in a MPEG compressed video sequence. In: Digital Video Compression: Algorithms and Technologies, vol. SPIE-2419, pp. 14–25 (1995)

    Google Scholar 

  16. Yeo, B., Liu, B.: Rapid scene analysis on compressed video. IEEE Transactions on Circuits and Systems for Video Technology 5(6), 533–540 (1995)

    Article  Google Scholar 

  17. Fernando, W.A.C., Canagarajah, C.N., Bull, D.R.: scene change detection algorithms for content-based video indexing and retrieval. Electronics and Communication Journal 13(3), 117–126 (2001)

    Google Scholar 

  18. Seong, Y.K., Choi, Y., Park, J., Choi, T.: A hard disk drive embedded digital satellite receiver with scene change detector for video indexing. IEEE Transactions on Consumer Electronics 48(3), 776–782 (2002)

    Article  Google Scholar 

  19. Sethi, I.K., Patal, N.: A statistical approach to scene change detection. In: Storage and Retrieval for Image and Video Databases III, vol. SPIE-2420, pp. 329–338 (1995)

    Google Scholar 

  20. Gargi, U., Kasturi, R., Strayer, S.H.: Performance Characterization of Video-Shot -Change Detection Methods. IEEE Transactions on Circuits and Systems for Video Technology 10(1), 1–13 (2000)

    Article  Google Scholar 

  21. Bescos, J., Cisneros, G., Menendez, J.M.: Multidemensional Comparison of Shot Detection Algorithms. In: Proceedings of International Conference on Image Processing, vol. 2, pp. II-404–II-404 (2002)

    Google Scholar 

  22. Bescos, J., Cisneros, G., Menendez, J.M., Cabrera, J.: A unified model for techniques on video-shot transition detection. IEEE transaction on Multimedia 7, 293–307 (2005)

    Article  Google Scholar 

  23. Cheng, Y., Yang, X., Xu, D.: A Method for Shot Boundary Detection With Automatic Threshold. Proceedings of IEEE TENCON 1, 582–585 (2002)

    Google Scholar 

  24. Ko, K.C., Rhee, Y.W.: Video Segmentation using the Automated Threshold Decision Algorithm. KSCI Journal 10(6), 65–73 (2005)

    Google Scholar 

  25. Boccignone, G., Chinaese, A., Moscato, V., Picariello, A.: Foveated Shot Detection for Video Segmentation. IEEE Transactions on Circuits and Systems for Video Technology 15, 365–377 (2005)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kim, WH., Kim, JN. (2010). Real-Time Adaptive Shot Change Detection Model. In: Kim, Th., Pal, S.K., Grosky, W.I., Pissinou, N., Shih, T.K., Ślęzak, D. (eds) Signal Processing and Multimedia. MulGraB SIP 2010 2010. Communications in Computer and Information Science, vol 123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17641-8_29

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-17641-8_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17640-1

  • Online ISBN: 978-3-642-17641-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics