Visual Saliency Computation: A Machine Learning Perspective

✍ Scribed by Jia Li, Wen Gao (auth.)

• Publisher: Springer International Publishing
• Year: 2014
• Tongue: English
• Leaves: 245
• Series: Lecture Notes in Computer Science 8408 Image Processing, Computer Vision, Pattern Recognition, and Graphics
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages -
Introduction....Pages 1-21
Benchmark and Evaluation Metrics....Pages 23-44
Location-Based Visual Saliency Computation....Pages 45-71
Object-Based Visual Saliency Computation....Pages 73-100
Learning-Based Visual Saliency Computation....Pages 101-149
Mining Cluster-Specific Knowledge for Saliency Ranking....Pages 151-178
Removing Label Ambiguity in Training Saliency Model....Pages 179-213
Saliency-Based Applications....Pages 215-232
Conclusions and Future Work....Pages 233-237
Back Matter....Pages -

✦ Subjects

Image Processing and Computer Vision; Artificial Intelligence (incl. Robotics); Data Mining and Knowledge Discovery