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A New Feasible Approach to Multi-dimensional Scale Saliency

  • Conference paper
Advanced Concepts for Intelligent Vision Systems (ACIVS 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5807))

Abstract

In this paper, we present a multi-dimensional extension of an image feature extractor, the scale saliency algorithm by Kadir and Brady. In order to avoid the curse of dimensionality, our algorithm is based on a recent Shannon’s entropy estimator and on a new divergence metric in the spirit of Friedman’s and Rafsky estimation of Henze-Penrose divergence. The experiments show that, compared to our previous existing method based on entropic graphs, this approach remarkably decreases computation time, while not significantly deterioring the quality of the results.

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Author information

Authors and Affiliations

  1. Robot Vision Group, Departamento de Ciencia de la Computación e IA, Universidad de Alicante, Spain

    Pablo Suau & Francisco Escolano

Authors
  1. Pablo Suau
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  2. Francisco Escolano
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Editor information

Editors and Affiliations

  1. DGA/D4S/MRIS, CEP/GIP, 16 bis avenue Prieur de la côte d’or., 94114, Arcueil, France

    Jacques Blanc-Talon

  2. Department of Telecommunication and Information Processing, Ghent University, St.-Pietersnieuwstraat 41, 9000, Gent, Belgium

    Wilfried Philips

  3. CSIRO ICT Centre, Epping, Po Box 76, 1710, Sydney, NSW, Australia

    Dan Popescu

  4. University of Antwerp, Universiteitsplein 1; Building N., 2610, Wilrijk, Belgium

    Paul Scheunders

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© 2009 Springer-Verlag Berlin Heidelberg

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Suau, P., Escolano, F. (2009). A New Feasible Approach to Multi-dimensional Scale Saliency. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2009. Lecture Notes in Computer Science, vol 5807. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04697-1_8

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  • DOI: https://doi.org/10.1007/978-3-642-04697-1_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04696-4

  • Online ISBN: 978-3-642-04697-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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