From Human Attention to Computational Attention

A Multidisciplinary Approach

  • Matei Mancas
  • Vincent P. Ferrera
  • Nicolas Riche
  • John G. Taylor

Part of the Springer Series in Cognitive and Neural Systems book series (SSCNS, volume 10)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Matei Mancas, Vincent P. Ferrera, Nicolas Riche
    Pages 1-6
  3. Foundations

    1. Front Matter
      Pages 7-7
    2. Matei Mancas
      Pages 9-20
    3. Matei Mancas, Vincent P. Ferrera
      Pages 21-38
    4. Tal Seidel Malkinson, Paolo Bartolomeo
      Pages 39-59
  4. Modeling

  5. Evolution and Applications

    1. Front Matter
      Pages 269-269
    2. Antoine Coutrot, Nathalie Guyader
      Pages 291-304

About this book

Introduction

This both accessible and exhaustive book will help to improve modeling of attention and to inspire innovations in industry. It introduces the study of attention and focuses on attention modeling, addressing such themes as saliency models, signal detection and different types of signals, as well as real-life applications. The book is truly multi-disciplinary, collating work from psychology, neuroscience, engineering and computer science, amongst other disciplines.

What is attention? We all pay attention every single moment of our lives. Attention is how the brain selects and prioritizes information. The study of attention has become incredibly complex and divided: this timely volume assists the reader by drawing together work on the computational aspects of attention from across the disciplines. Those working in the field as engineers will benefit from this book’s introduction to the psychological and biological approaches to attention, and neuroscientists can learn about engineering work on attention. The work features practical reviews and chapters that are quick and easy to read, as well as chapters which present deeper, more complex knowledge. Everyone whose work relates to human perception, to image, audio and video processing will find something of value in this book, from students to researchers and those in industry. 

Keywords

Attention Modeling Saliency Models Brain Attention Signal Detection Attention Applications Image, Video, 3D, Audio Signals

Editors and affiliations

  • Matei Mancas
    • 1
  • Vincent P. Ferrera
    • 2
  • Nicolas Riche
    • 3
  • John G. Taylor
    • 4
  1. 1.Numediart InstituteUniversity of MonsMonsBelgium
  2. 2.Columbia UniversityNew YorkUSA
  3. 3.Numediart InstituteUniversity of MonsMONSBelgium
  4. 4.King's CollegeLONDONUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4939-3435-5
  • Copyright Information Springer Science+Business Media New York 2016
  • Publisher Name Springer, New York, NY
  • eBook Packages Biomedical and Life Sciences
  • Print ISBN 978-1-4939-3433-1
  • Online ISBN 978-1-4939-3435-5
  • Series Print ISSN 2363-9105
  • Series Online ISSN 2363-9113
  • About this book