Skip to main content

vManager, Developing a Complete CBVR System

  • Conference paper
Pattern Recognition and Image Analysis (IbPRIA 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6669))

Included in the following conference series:

  • 3020 Accesses

Abstract

Content-Based Video Retrieval (CBVR) is a research area that has drawn a good deal of attention in recent years. The ability to retrieve videos similar to a given one in terms of implicit features (mainly pictorial features) and/or explicit characteristics (eg. semantic context) are the cornerstones of this growing interest. In this paper we present the results obtained within the project vManager, a CBVR system based on local color and motion signatures, our own video representation and different metrics of similarity among videos. The results for real videos point to promising advances, not only as regards the effectiveness of the system, but also in terms of its efficiency.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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. Hampapur, A., Hyun, K.H., Bolle, R., Ferman, A.M., Tekalp, A.M., Mehrotra, R.: Robust Color Histogram Descriptors for Video Segment Retrieval and Identification. IEEE Transactions on Image Processing 11(5), 497–508 (2002)

    Article  Google Scholar 

  2. Lee, H.-C., Kim, S.-D.: Rate-Driven Key Frame Selection Using Temporal Variation of Visual Content. Electronics Letters 38(5), 217–218 (2002)

    Article  Google Scholar 

  3. Zhai, Y., Liu, J., Cao, X.: Video understanding and content-based retrieval. School of Computer Science (2005)

    Google Scholar 

  4. Shiitani, S., Baba, T., Endo, S., Uehara, Y., Masumoto, D., Nagata, S.: Efficient video retrieval system using virtual 3D space. In: 6th IEEE Southwest Symposium on Image Analysis and Interpretation, pp. 206–210 (2004)

    Google Scholar 

  5. Kim, J., Lim, H., Kang, D.: An implementation of the video retrieval system by video segmentation. In: 14th Asia-Pacific Conference on Communications, pp. 1–5 (2008)

    Google Scholar 

  6. Nguyen, D.T., Gillespie, W.: A video retrieval system based on compressed data from MPEG files. In: Conference on Convergent Technologies for Asia-Pacific Region, pp. 555–560 (2003)

    Google Scholar 

  7. Vakkalanka, S., Palanivel, S., Yegnanarayana, B.: NVIBRS - news video indexing, browsing and retrieval system. Intelligent Sensing and Information Processing, 181–186 (2005)

    Google Scholar 

  8. Camara-Chavez, G., Precioso, F., Cord, M., Phillip-Foliguet, S., de Araujo, A.: An interactive video content-based retrieval system. In: 15th International Conference on Systems, Signals and Image Processing, pp. 133–136 (2008)

    Google Scholar 

  9. Zhou, X., Zhou, X., Shen, H.T.: Efficient similiarity search by summarization in large video database. In: School of Information Technology and Electrical Engineering (2007)

    Google Scholar 

  10. Zagorac, S., Llorente, A., Little, S., Liu, H., Rueger, S.: Automated Content Based Video Retrieval, TREC Video Retrieval Evaluation Notebook Papers (2009)

    Google Scholar 

  11. Hua, X., Yin, P., Wang, H., Chen, J., Mingjing, L., Li, M., Zhang, H.: MSR-Asia TREC-11 video track. In: Proceedings of the Text Retrieval Conference (2002)

    Google Scholar 

  12. Zampoglou, M., Papadimitriou, T., Diamantaras, K.I.: Integrating motion and color for content based video classification. In: Proceedings of IEEE Intl. Conf. on Image Processing (2008)

    Google Scholar 

  13. Kim, C., Vasudev, B.: Spatiotemporal sequence matching for efficient video copy detection. IEEE Transactions on Circuits and Systems for Video Technology 15(1), 127–132 (2005)

    Article  Google Scholar 

  14. Cinque, L., Levialdi, S., Olsen, K.A., Pellinaco, A.: Color-Based Image Retrieval Using Spatial-Chromatic Histograms. Image and Vision Computing 19, 979–986 (2001)

    Article  Google Scholar 

  15. Dimitrovski, I., Loskovska, S., Kalasevski, G., Chorbev, I.: Video Contet-Based Retrieval System. In: EUROCON, The International Conference on ”Computer as a Tool”, pp. 978–983 (2007)

    Google Scholar 

  16. Huang, C.-L., Liao, B.-Y.: A Robust Scene-Change Detection Method for Video Segmentation. IEEE Transactions on Circuits and Systems for Video Technology 11(12), 1281–1288 (2001)

    Article  Google Scholar 

  17. Huang, Z., Shen, H.T., Shao, J., Zhou, X., Cui, B.: Bounded Coordinate System Indexing for Real-Time Video Clip Search. ACM Transactions on Information Systems 27(3), 17.1–17.33 (2009)

    Article  Google Scholar 

  18. Zabih, R., Miller, J., Mai, K.: A Feature-Based Algorithm for Detecting and Classifying Scene Breaks. In: Third ACM International Conference on Multimedia, pp. 189–200 (1995)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Caro, A., Rodríguez, P.G., Morcillo, R., Barrena, M. (2011). vManager, Developing a Complete CBVR System. In: Vitrià, J., Sanches, J.M., Hernández, M. (eds) Pattern Recognition and Image Analysis. IbPRIA 2011. Lecture Notes in Computer Science, vol 6669. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21257-4_75

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-21257-4_75

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21256-7

  • Online ISBN: 978-3-642-21257-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics