Abstract
This paper assesses the usefulness of surface features in a multimedia retrieval setting. Surface features describe the metadata or structure of a document rather than the content. We note that the distribution of these features varies across topics. The paper shows how these distributions can be obtained through relevance feedback and how this allows for adaptation of (content-based) search results for topic or user preference. An analysis of the distribution of surface features in the TRECVID collection indicates that they are potentially useful, and a preliminary feedback experiment confirms that exploiting surface features can improve retrieval effectiveness.
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© 2006 Springer-Verlag Berlin Heidelberg
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Westerveld, T., de Vries, A.P., Ramírez, G. (2006). Surface Features in Video Retrieval. In: Detyniecki, M., Jose, J.M., Nürnberger, A., van Rijsbergen, C.J. (eds) Adaptive Multimedia Retrieval: User, Context, and Feedback. AMR 2005. Lecture Notes in Computer Science, vol 3877. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11670834_15
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DOI: https://doi.org/10.1007/11670834_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32174-3
Online ISBN: 978-3-540-32175-0
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