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Visual Saliency Computation pp 101–149Cite as

Learning-Based Visual Saliency Computation

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8408))

Abstract

In this Chapter, we describe how to model the top-down factors in human vision system. Usually, such top-down factors should be learned from user data such as fixations or labeled salient objects by using machine learning algorithms. Therefore, we will present how to model various top-down factors by using supervised or unsupervised learning algorithms. Moreover, we aim to show how the machine learning algorithms can help to improve the performance of saliency models.

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Authors and Affiliations

  1. Peking University, Haidian District, 100871, Beijing, China

    Jia Li & Wen Gao

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  1. Jia Li
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  2. Wen Gao
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Li, J., Gao, W. (2014). Learning-Based Visual Saliency Computation. In: Visual Saliency Computation. Lecture Notes in Computer Science, vol 8408. Springer, Cham. https://doi.org/10.1007/978-3-319-05642-5_5

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  • DOI: https://doi.org/10.1007/978-3-319-05642-5_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05641-8

  • Online ISBN: 978-3-319-05642-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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