Skip to main content
SpringerLink
Log in
SpringerLink
Log in

Shot Classification Using Domain Specific Features for Movie Management

  • Conference paper
Database Systems for Advanced Applications (DASFAA 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7239))

Included in the following conference series:

Abstract

Among many video types, movie content indexing and retrieval is a significantly challenging task because of the wide variety of shooting techniques and the broad range of genres. A movie consists of a series of video shots. Managing a movie at shot level provides a feasible way for movie understanding and summarization. Consequently, an effective shot classification is greatly desired for advanced movie management. In this demo, we explore novel domain specific features for effective shot classification. Experimental results show that the proposed method classifies movie shots from wide range of movie genres with improved accuracy compared to existing work.

This research was supported by National Natural Science Foundation of China No. 61003161 and UTS ECR grant.

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

Access this chapter

Log in via an institution
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. Shi, L., Wang, J., Xu, L., Lu, H., Xu, C.: Context saliency based image summarization. In: Proceedings of the IEEE ICME, pp. 270–273 (2009)

    Google Scholar 

  2. Huang, C., Ai, H., Li, Y., Lao, S.: Vector boosting for rotation invariant multi-view face detection. In: Proceedings of the IEEE ICCV, vol. 1 (2005)

    Google Scholar 

  3. Kapur, J.N., Sahoo, P.K., Wong, A.K.C.: A New Method for Gray-Level Picture Thresholding Using the Entropy of the Histogram. Computer Vision, Graphics, and Image Processing 29(3), 273–285 (1985)

    Article  Google Scholar 

  4. Cantine, J., Lewis, B., Howard, S.: Shot by Shot; A Practical Guide to Filmmaking, Pittsburgh Filmmakers (1995)

    Google Scholar 

  5. Xu, M., Wang, J., Hasan, M.A., He, X., Xu, C., Lu, H., Jin, J.S.: Using Context Saliency for Movie Shot Classification. In: Proceedings of the IEEE ICIP (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Centre for Innovation in IT Services and Applications (iNEXT), University of Technology, Sydney, PO Box 123, Broadway, NSW, 2007, Australia

    Muhammad Abul Hasan, Min Xu & Xiangjian He

  2. Centre for Quantum Computation and Intelligent Systems (QCIS), University of Technology, Sydney, PO Box 123, Broadway, NSW, 2007, Australia

    Ling Chen

Authors
  1. Muhammad Abul Hasan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Min Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiangjian He
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ling Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Computer Science and Engineering, Seoul National University, Gwanak-ro, Gwanak-gu, 151747, Seoul, South Korea

    Sang-goo Lee

  2. Computer School, Wuhan University, Luo-jia-shan, Wuchang, 430081, Wuhan, Hubei Province, China

    Zhiyong Peng

  3. School of Information Technology and Electrical Engineering, University of Queensland, 4072, Brisbane, QLD, Australia

    Xiaofang Zhou

  4. Department of Computer Science, Kangwon National University, 192-1, Hyoja2-Dong, 200701, Chuncheon, Kangwon, South Korea

    Yang-Sae Moon

  5. Institute for Computer Science and Business Information, University of Duisburg-Essen, Schützenbahn 70, 45117, Essen, Germany

    Rainer Unland

  6. School of Information and Communication Engineering, Chungbuk National University, 52 Naesudong-ro, Heungdeok-gu, 4072, Cheongju, Chungbuk, South Korea

    Jaesoo Yoo

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Hasan, M.A., Xu, M., He, X., Chen, L. (2012). Shot Classification Using Domain Specific Features for Movie Management. In: Lee, Sg., Peng, Z., Zhou, X., Moon, YS., Unland, R., Yoo, J. (eds) Database Systems for Advanced Applications. DASFAA 2012. Lecture Notes in Computer Science, vol 7239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29035-0_28

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-29035-0_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29034-3

  • Online ISBN: 978-3-642-29035-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation