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Innovations in Intelligent Image Analysis pp 59–85Cite as

Task-Specific Salience for Object Recognition

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 339))

Abstract

Object recognition is a complex and challenging problem. It involves examining many different hypothesis in terms of the object class, position, scale, pose, etc., but the main trend in computer vision systems is to lazily rely on the brute force capacity of computers, that is to explore every possibilities indifferently. Sadly, in many case this scheme is way too slow for real-time or even practical applications. By incorporating salience in the recognition process, several approaches have shown that it is possible to get several orders of speed-up. In this chapter, we demonstrate the link between salience and cascaded processes and show why and how those ones should be constructed. We illustrate the benefits that it provides, in terms of detection speed, accuracy and robustness, and how it eases the combination of heterogeneous feature types (i.e. dense and sparse features) by some innovating strategies from the state-of-the-art and a practical application.

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Author information

Authors and Affiliations

  1. INSA-Lyon, LIRIS, UMR5205, Universite de Lyon, CNRS, F-69621, France

    Jerome Revaud, Guillaume Lavoue & Atilla Baskurt

  2. CS17 Media Laboratory, Kobe University, Japan

    Yasuo Ariki

Authors
  1. Jerome Revaud
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  2. Guillaume Lavoue
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  3. Yasuo Ariki
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  4. Atilla Baskurt
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Editor information

Editors and Affiliations

  1. Deputy Director for Scientific Researches Institute of Informatics, Wroclaw University of Technology , Wyb. Wyspianskiego 27, 51-370, Wroclaw, Poland

    Halina Kwaśnicka

  2. Founding Director of the KES Centre School of Electrical and Information Engineering, Knowledge-Based Engineering University of South Australia Adelaide , Mawson Lakes Campus, 5095, South Australia, SA, Australia

    Lakhmi C. Jain

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Revaud, J., Lavoue, G., Ariki, Y., Baskurt, A. (2011). Task-Specific Salience for Object Recognition. In: Kwaśnicka, H., Jain, L.C. (eds) Innovations in Intelligent Image Analysis. Studies in Computational Intelligence, vol 339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17934-1_4

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  • DOI: https://doi.org/10.1007/978-3-642-17934-1_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17933-4

  • Online ISBN: 978-3-642-17934-1

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