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Boundary Error Analysis and Categorization in the TRECVID News Story Segmentation Task

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Image and Video Retrieval (CIVR 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3568))

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Abstract

In this paper, an error analysis based on boundary error popularity (frequency) including semantic boundary categorization is applied in the context of the news story segmentation task from TRECVID. Clusters of systems were defined based on the input resources they used including video, audio and automatic speech recognition. A cross-popularity specific index was used to measure boundary error popularity across clusters, which allowed goal-driven selection of boundaries to be categorized. A wide set of boundaries was viewed and a summary of the error types is presented. This framework allowed conclusions about the behavior of resource-based clusters in the context of news story segmentation.

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References

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Author information

Authors and Affiliations

  1. Departament d’Informàtica de Sistemes i Computadors, Universitat Politècnica de València, Cami de Vera s/n, 46022, València, Spain

    Joaquim Arlandis

  2. Retrieval Group, Information Access Division, National Institute of Standards and Technology, Gaithersburg, MD, 20899-8940, USA

    Paul Over

  3. Department of Data Interpretation, Information Systems Division, TNO Science & Industry, 2600 AD, Delft, The Netherlands

    Wessel Kraaij

Authors
  1. Joaquim Arlandis
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  2. Paul Over
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  3. Wessel Kraaij
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Editor information

Editors and Affiliations

  1. Dept. of Computer Science, National University of Singapore, Computing 1, 117590, Singapore

    Wee-Kheng Leow

  2. LIACS Media Lab, Leiden University,  

    Michael S. Lew  & Erwin M. Bakker  & 

  3. National University of Singapore, 3 Science Dr, 117543, Singapore

    Tat-Seng Chua

  4. Microsoft Research Asia, 4F, Sigma Center, No.49, Zhichun Road, 100080, Beijing, P.R.China

    Wei-Ying Ma

  5. School of Computing, National University of Singapore, 3 Science Drive 2, 117543, Singapore

    Lekha Chaisorn

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© 2005 Springer-Verlag Berlin Heidelberg

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Arlandis, J., Over, P., Kraaij, W. (2005). Boundary Error Analysis and Categorization in the TRECVID News Story Segmentation Task. In: Leow, WK., Lew, M.S., Chua, TS., Ma, WY., Chaisorn, L., Bakker, E.M. (eds) Image and Video Retrieval. CIVR 2005. Lecture Notes in Computer Science, vol 3568. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11526346_14

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  • DOI: https://doi.org/10.1007/11526346_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27858-0

  • Online ISBN: 978-3-540-31678-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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