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. 

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. 

Foreword

V. Cutsuridis

Introduction
1 Why modeling attention in computers?
M. Mancas, V. Ferrera, N. Riche

Part 1: Foundations
2  What is attention?
M. Mancas

3 How to measure attention?
M. Mancas, V. Ferrera

4 Where: Human attention networks and their dysfunctions after brain damage
T. Seidel Malkinson, P. Bartolomeo

Part 2: Modeling
5 Attention and Signal Detection: A Practical Guide
V. Ferrera

6 Effects of Attention in Visual Cortex: Linking Single Neuron Physiology to Visual Detection and Discrimination
V. Ferrera

7 Modeling attention in engineering
M. Mancas

8 Bottom-Up Visual Attention for Still Images: a Global View
F. Stentiford

9 Bottom-up saliency models for still images: a practical review
N. Riche and M. Mancas

10 Bottom-up saliency models for videos: a practical review
N. Riche and M. Mancas

11 Databases for sal

iency models evaluation
N. Riche

12 Metrics for saliency models validation
N. Riche

13 Study of parameters affecting visual saliency assessment
N. Riche

14 Saliency models evaluation
N. Riche

Part 3: Evolution and Applications
15 Object-based Attention: cognitive and computational perspectives
A. Belardinelli

16 Multimodal saliency models for videos
Antoine Coutrot, Nathalie Guyader

17 Towards 3D visual saliency modelling
J. Leroy, N. Riche

18 Applications of saliency models
M. Mancas, O. Le Meur

19 Attentive Content-Based Image Retrieval
D. Awad, V. Courboulay, A. Revel

20 Saliency and Attention for Video Quality Assessment
D. Culibrk

21 Attentive Robots
S. Frintrop

Conclusion:
22 Attention modeling: what are the next steps?
M. Mancas, V. Ferrera, N. RIche

Index