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Visual Content Indexing and Retrieval with Psycho-Visual Models

  • Jenny Benois-Pineau
  • Patrick Le Callet

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

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Patrick Le Callet, Jenny Benois-Pineau
    Pages 1-10
  3. Karam Naser, Vincent Ricordel, Patrick Le Callet
    Pages 11-41
  4. Souad Chaabouni, Jenny Benois-Pineau, Akka Zemmari, Chokri Ben Amar
    Pages 43-74
  5. Syntyche Gbehounou, Thierry Urruty, François Lecellier, Christine Fernandez-Maloigne
    Pages 75-101
  6. Michael Dorr, Eleonora Vig
    Pages 103-124
  7. Axel Carlier, Lilian Calvet, Pierre Gurdjos, Vincent Charvillat, Wei Tsang Ooi
    Pages 125-144
  8. Adrian G. Bors, Alex Papushoy
    Pages 171-209
  9. Pol Kennel, Frédéric Comby, William Puech
    Pages 211-232
  10. Claire-Hélène Demarty, Mats Sjöberg, Mihai Gabriel Constantin, Ngoc Q. K. Duong, Bogdan Ionescu, Thanh-Toan Do et al.
    Pages 233-265
  11. Back Matter
    Pages 267-267

About this book

Introduction

This book provides a deep analysis and wide coverage of the very strong trend in computer vision and visual indexing and retrieval, covering such topics as incorporation of models of Human Visual attention into analysis and retrieval tasks. It makes the bridge between psycho-visual modelling of Human Visual System and the classical and most recent models in visual content indexing and retrieval.

The large spectrum of visual tasks, such as recognition of textures in static images, of actions in video content, image retrieval, different methods of visualization of images and multimedia content based on visual saliency are presented by the authors. Furthermore, the interest in visual content is modelled with the means of the latest classification models such as Deep Neural Networks is also covered in this book.

This book is an exceptional resource as a secondary text for researchers and advanced level students, who are involved in the very wide research in computer vision, visual information indexing and retrieval. Professionals working in this field will also be interested in this book as a reference.

Keywords

Visual attention modeling Selection of relevant features Interestingness of the content Machine learning with Deep NN Visual similarity Interestingness Salient features 3D saliency maps Saliency-Based Visualization Perceptual similarity Visual Content Indexing Retrieval Psycho-Visual Models

Editors and affiliations

  • Jenny Benois-Pineau
    • 1
  • Patrick Le Callet
    • 2
  1. 1.LaBRI UMR 5800, Univ. Bordeaux, CNRS, Bordeaux INPUniv. BordeauxTalenceFrance
  2. 2.LS2N, UMR CNRS 6004Université de NantesNantes Cedex 3France

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-57687-9
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-57686-2
  • Online ISBN 978-3-319-57687-9
  • Buy this book on publisher's site
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