Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Video Querying

  • Ichiro IdeEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_1030


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


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 to check access.

Recommended Reading

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

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Graduate School of InformaticsNagoya UniversityNagoyaJapan

Section editors and affiliations

  • Vincent Oria
    • 1
  • Shin'ichi Satoh
    • 2
  1. 1.Dept. of Computer ScienceNew Jersey Inst. of TechnologyNewarkUSA
  2. 2.Digital Content and Media Sciences ReseaMultimedia Information Research DivisionNational Institute of InformaticsTokyoJapan