From human attention to computational attention [electronic resource] : a multidisciplinary approach / Matei Mancas, Vincent P. Ferrera, Nicolas Riche, John G. Taylor, editors.
Mancas, Matei, editor.; Ferrera, Vincent P., editor.; Riche, Nicolas, editor.; Taylor, J. G. (John Gerald), 1931-2012, editor.
2016
RC321-580
Available Online

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Title From human attention to computational attention [electronic resource] : a multidisciplinary approach / Matei Mancas, Vincent P. Ferrera, Nicolas Riche, John G. Taylor, editors.
ISBN 9781493934355 (electronic book)
9781493934331
DOI https://doi.org/10.1007/978-1-4939-3435-5
Published New York, NY : Springer, [2016]
Copyright ©2016
Language English
Description 1 online resource (viii, 463 pages) : illustrations
Other Standard Identifiers 10.1007/978-1-4939-3435-5 doi
Call Number RC321-580
Dewey Decimal Classification 006.3
Summary 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. .
Bibliography, etc. Note Includes bibliographic references and index.
Access Note Access limited to authorized users.
Digital File Characteristics text file PDF
Added Author Mancas, Matei, editor.
Ferrera, Vincent P., editor.
Riche, Nicolas, editor.
Taylor, J. G. (John Gerald), 1931-2012, editor.
Series Springer series in cognitive and neural systems ; 10.
Available in Other Form Print version: 9781493934331
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
Why do computers need attention? / Matei Mancas, Vincent P. Ferrera, and Nicolas Riche
What is attention? / Matei Mancas
How to measure attention? / Matei Mancas and Vincent P. Ferrera
Where: Human attention networks and their dysfunctions after brain damage / Tal Seidel Malkinson and Paolo Bartolomeo
Attention and signal detection: a practical guide / Vincent P. Ferrera
Effects of attention in visual cortex: linking single neuron physiology to visual detection and discrimination / Vincent P. Ferrera
Modeling attention in engineering / Matei Mancas
Bottom-up visual attention for still images: a global view / Fred Stentiford
Bottom-up saliency models for still images: a practical review / Nicolas Riche and Matei Mancas
Bottom-up saliency models for videos: a practical review / Nicolas Riche and Matei Mancas
Databases for saliency model evaluation / Nicolas Riche
Metrics for saliency model validation, Nicolas Riche
Study of parameters affecting visual saliency assessment / Nicolas Riche
Saliency model evaluation / Nicolas Riche
Object-based attention: cognitive and computational perspectives / Anna Belardinelli
Multimodal saliency models for videos / Antoine Coutrot and Nathalie Guyader
Toward 3D visual saliency modeling / Leroy Julien and Nicolas Riche
Applications of saliency models / Matei Mancas and Olivier Le Meur
Attentive content-based image retrieval / Dounia Awad, Vincent Courboulay, and Arnaud Revel
Saliency and attention for video quality assessment / Dubravko Culibrk
Attentive robots / Simone Frintrop
The future of attention models: information seeking and self-awareness / Matei Mancas, Vincent P. Ferrera, and Nicolas Riche
Index.

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