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Visual Content Indexing and Retrieval with Psycho-Visual Models pp 1–10Cite as

Visual Content Indexing and Retrieval with Psycho-Visual Models

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Part of the book series: Multimedia Systems and Applications ((MMSA))

Abstract

The present chapter is an introduction to the book. The subject we propose has seen an exploded interest since last decade from research community in computer vision and multimedia indexing. From the field of video quality assessment where models of Human Visual System (HVS) were generally used to predict where humans will foveate and how will they perceive the degradation, these methods moved to classical Image and Video Indexing and retrieval tasks, recognition of objects, events, actions in images and video. In this book we try to give the most complete overview of the methods for visual information indexing and retrieval using prediction of visual attention or saliency. But also consider new approaches specifically designed for these tasks.

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Author information

Authors and Affiliations

  1. LS2N UMR CNRS 6004, Université de Nantes, Nantes Cedex 3, France

    Patrick Le Callet

  2. LaBRI UMR 5800, Univ. Bordeaux, CNRS, Bordeaux INP, Univ. Bordeaux, 351, crs de la Liberation, F33405, Talence Cedex, France

    Jenny Benois-Pineau

Authors
  1. Patrick Le Callet
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  2. Jenny Benois-Pineau
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Corresponding author

Correspondence to Patrick Le Callet .

Editor information

Editors and Affiliations

  1. LaBRI UMR 5800, Univ. Bordeaux, CNRS, Bordeaux INP, Univ. Bordeaux, Talence, France

    Jenny Benois-Pineau

  2. LS2N, UMR CNRS 6004, Université de Nantes, Nantes Cedex 3, France

    Patrick Le Callet

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Le Callet, P., Benois-Pineau, J. (2017). Visual Content Indexing and Retrieval with Psycho-Visual Models. In: Benois-Pineau, J., Le Callet, P. (eds) Visual Content Indexing and Retrieval with Psycho-Visual Models. Multimedia Systems and Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-57687-9_1

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  • DOI: https://doi.org/10.1007/978-3-319-57687-9_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-57686-2

  • Online ISBN: 978-3-319-57687-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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