Skip to main content
SpringerLink
Log in

Video Querying

  • Living reference work entry
  • First Online:
Encyclopedia of Database Systems

  • 102 Accesses

Synonyms

Image querying; Near-duplicate video retrieval; Query by example; Similarity in video

Definition

Video querying is a way to issue a query for retrieving video data from a database without explicitly expressing the contents of the video-in-search by high-level semantics, such as keywords. It, instead, expects that a user issues a query as a video segment in hand. The system will then search and retrieve similar video data from the database. Since video data is composed of sequences of still-frame images, the search for similar video data in a database necessarily requires a huge computation cost when comparing the query with the data in the database. Thus, the main issue when processing a video query is to reduce both the computation time for the search itself and for the comparison of image sequences, to evaluate the similarity of the video segments. Video querying is an efficient way to issue a query when a user already has in hand an exact or an extremely relevant segment of...

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

Access this chapter

Log in via an institution

Institutional subscriptions

Recommended Reading

  1. Aghbari Z, Kaneko K, Makinouchi A. Content-trajectory approach for searching video databases. IEEE Trans Multimed. 2003;5(4):516–31.

    Article  Google Scholar 

  2. Chang S-F, Chen W, Meng HJ, Sundaran H, Zhong D. VideoQ: an automated content based video search system using visual cues. In: Proceedings of the 5th ACM International Conference on Multimedia; 1997. p. 313–24.

    Google Scholar 

  3. Dimitrova N, Abdel-Mottaleb M. Content-based video retrieval by example video clip. In: Proceedings of the Storage and Retrieval for Image and Video Database; 1997. p. 59–70.

    Google Scholar 

  4. Kashino K, Kurozumi T, Murase H. A quick search method for audio and video signals based on histogram pruning. IEEE Trans Multimed. 2003;5(3):348–57.

    Article  Google Scholar 

  5. Lienhart R, Effelsberg W, Jain R. VisualGREP: a systematic method to compare and retrieve video sequences. Multime Tool Appl, Kluwer, Hingham, MA. 2000;10(1):47–72.

    Article  Google Scholar 

  6. Lienhart R, Kuhmünch C, Effelsberg W. On the detection and recognition of television commercials. In: Proceedings of the International Conference on Multimedia Computing and Systems; 1997. p. 509–16.

    Google Scholar 

  7. Liu J-J, Huang Z, Cai H-Y, Shen H-T, Ngo C-W, Wang W. Near-duplicate video retrieval: current research and future trends. ACM Comput Surv. 2013;45(4):44:1–44:23.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Graduate School of Informatics, Nagoya University, 1 Furo-cho, Chikusa-ku, 464-8601, Nagoya, Aichi, Japan

    Ichiro Ide

Authors
  1. Ichiro Ide
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ichiro Ide .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, Georgia, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, Ontario, Canada

    M. Tamer Özsu

Section Editor information

  1. Dept. of Computer Science, New Jersey Inst. of Technology, University Heights, 7102, Newark, NJ, USA

    Vincent Oria

  2. Digital Content and Media Sciences ReseaMultimedia Information Research Division, National Institute of Informatics, Tokyo, Japan

    Shin'ichi Satoh

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Science+Business Media LLC

About this entry

Cite this entry

Ide, I. (2017). Video Querying. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_1030-2

Download citation

  • DOI: https://doi.org/10.1007/978-1-4899-7993-3_1030-2

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4899-7993-3

  • Online ISBN: 978-1-4899-7993-3

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

Publish with us

Policies and ethics

Search

Navigation