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Visual Saliency Computation

A Machine Learning Perspective

  • Book
  • © 2014

Overview

Authors:
  1. Jia Li

    1. Peking University, Beijing, China

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    You can also search for this author in PubMed   Google Scholar

  2. Wen Gao

    1. Peking University, Beijing, China

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    You can also search for this author in PubMed   Google Scholar

  • 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)

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Table of contents (9 chapters)

  1. Front Matter

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  2. Introduction

    • Jia Li, Wen Gao
    Pages 1-21

  3. Benchmark and Evaluation Metrics

    • Jia Li, Wen Gao
    Pages 23-44

  4. Location-Based Visual Saliency Computation

    • Jia Li, Wen Gao
    Pages 45-71

  5. Object-Based Visual Saliency Computation

    • Jia Li, Wen Gao
    Pages 73-100

  6. Learning-Based Visual Saliency Computation

    • Jia Li, Wen Gao
    Pages 101-149

  7. Mining Cluster-Specific Knowledge for Saliency Ranking

    • Jia Li, Wen Gao
    Pages 151-178

  8. Removing Label Ambiguity in Training Saliency Model

    • Jia Li, Wen Gao
    Pages 179-213

  9. Saliency-Based Applications

    • Jia Li, Wen Gao
    Pages 215-232

  10. Conclusions and Future Work

    • Jia Li, Wen Gao
    Pages 233-237

  11. Back Matter

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Keywords

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.

Authors and Affiliations

  • Peking University, Beijing, China

    Jia Li, Wen Gao

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