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Object Recognition for Video Retrieval

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Image and Video Retrieval (CIVR 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2383))

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Abstract

Recognition of objects in video can offer significant benefits to video retrieval including automatic annotation and content based queries based on the object characteristics. This paper describes our preliminary work toward recognizing objects in video sequences and gives a brief survey of the relevant research in the literature. We use the Kalman filter to obtain segmented blobs from the video, classify the blobs using the probability ratio test, and apply several different temporal filtering methods, which results in sequential classification methods over the video sequence containing the blob. Results from real video sequences are shown.

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Author information

Authors and Affiliations

  1. LIACS Media Lab, Leiden University, Niels Bohrweg 1, 2300 CA, Leiden, The Netherlands

    Rene Visser, Nicu Sebe & Erwin Bakker

Authors
  1. Rene Visser
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  2. Nicu Sebe
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  3. Erwin Bakker
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Editor information

Editors and Affiliations

  1. LIACS Media Lab, Leiden University, Niels Bohrweg 1, 2333 CA, Leiden, The Netherlands

    Michael S. Lew  & Nicu Sebe  & 

  2. Institute for Image Data Research, University of Northumbria, Newcastle, NE1 8ST, UK

    John P. Eakins

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© 2002 Springer-Verlag Berlin Heidelberg

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Visser, R., Sebe, N., Bakker, E. (2002). Object Recognition for Video Retrieval. In: Lew, M.S., Sebe, N., Eakins, J.P. (eds) Image and Video Retrieval. CIVR 2002. Lecture Notes in Computer Science, vol 2383. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45479-9_28

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  • DOI: https://doi.org/10.1007/3-540-45479-9_28

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43899-1

  • Online ISBN: 978-3-540-45479-3

  • eBook Packages: Springer Book Archive

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