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From Human Attention to Computational Attention

A Multidisciplinary Approach

  • Book
  • © 2016

Overview

  • Enables readers to access attention modeling work across the disciplines and communities
  • Balances work on theory and practical applications in order to deepen understanding of attention
  • Supports communication between disciplines involved in attention modeling
  • Marks out avenues for future research and applications in computational attention
  • Aids faster testing and improvement of existing attention models

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

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Table of contents (22 chapters)

  1. Foundations

  2. Evolution and Applications

Keywords

About this book

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. 

Editors and Affiliations

  • Numediart Institute, University of Mons, Mons, Belgium

    Matei Mancas

  • Columbia University, New York, USA

    Vincent P. Ferrera

  • Numediart Institute, University of Mons, MONS, Belgium

    Nicolas Riche

  • King's College, LONDON, United Kingdom

    John G. Taylor

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