Overview
- Written to be easily understood by a wide range of readers, from specialists in the field of visual saliency computation to general readers interested in computer science and cognitive psychology
- Offers a foreword by Zhengyou Zhang, included in the front matter and is freely available for perusal on SpringerLink
- Introduces concepts step-by-step, starting from visual saliency and progressively exploring the problems in modeling saliency, extracting salient objects, mining prior knowledge, evaluating performance, and using saliency in real-world applications
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 8408)
Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
About this book
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.
Similar content being viewed by others
Keywords
Table of contents (9 chapters)
-
Front Matter
-
Back Matter
Authors and Affiliations
Bibliographic Information
Book Title: Visual Saliency Computation
Book Subtitle: A Machine Learning Perspective
Authors: Jia Li, Wen Gao
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-319-05642-5
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Softcover ISBN: 978-3-319-05641-8Published: 15 May 2014
eBook ISBN: 978-3-319-05642-5Published: 12 April 2014
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XII, 240
Number of Illustrations: 100 b/w illustrations
Topics: Image Processing and Computer Vision, Artificial Intelligence, Data Mining and Knowledge Discovery