
Visual Saliency Computation
A Machine Learning Perspective
Published on 15. May 2014
Book
Paperback/Softback
XII, 240 pages
978-3-319-05641-8 (ISBN)
Description
This book covers fundamental principles and computational approaches relevant to visual saliency computation. As an interdisciplinary problem, visual saliency computation is introduced in this book from an innovative perspective that combines both neurobiology and machine learning. The book is also well-structured to address a wide range of readers, from specialists in the field to general readers interested in computer science and cognitive psychology. With this book, a reader can start from the very basic question of "what is visual saliency?" and progressively explore the problems in detecting salient locations, extracting salient objects, learning prior knowledge, evaluating performance, and using saliency in real-world applications. It is highly expected that this book will spark a great interest of research in the related communities in years to come.
More details
Series
Edition
2014 ed.
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Research
Illustrations
100 s/w Abbildungen
XII, 240 p. 100 illus.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 14 mm
Weight
388 gr
ISBN-13
978-3-319-05641-8 (9783319056418)
DOI
10.1007/978-3-319-05642-5
Schweitzer Classification
Other editions
Additional editions

E-Book
04/2014
Springer
€53.49
Available for download
Content
Benchmark and evaluation metrics.- Location-based visual saliency computation.- Object-based visual saliency computation.- Learning-based visual saliency computation.- Mining cluster-specific knowledge for saliency ranking.- Removing label ambiguity in training saliency model.- Saliency-based applications.- Conclusions and future work.