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Multimedia Analysis by Learning

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4577))

Abstract

In this presentation for the panel at MCAM07, I put forward the transition of modeling the world as was done on a large scale in computer vision before the year 2000, to the current situation where there have been considerable successes with multimedia analysis by learning from the world. We make a plead for the last type of learned features, modeling only the scene accidental conditions and learning the object or object class intrinsic properties. In this paper, in respect to contributions by many others, we illustrate the approach of learning features by papers from our lab at the University of Amsterdam.

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References

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Nicu Sebe Yuncai Liu Yueting Zhuang Thomas S. Huang

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© 2007 Springer Berlin Heidelberg

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Smeulders, A.W.M. (2007). Multimedia Analysis by Learning. In: Sebe, N., Liu, Y., Zhuang, Y., Huang, T.S. (eds) Multimedia Content Analysis and Mining. MCAM 2007. Lecture Notes in Computer Science, vol 4577. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73417-8_1

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  • DOI: https://doi.org/10.1007/978-3-540-73417-8_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73416-1

  • Online ISBN: 978-3-540-73417-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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