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Saliency Detection via Foreground and Background Seeds

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Information Science and Applications 2017 (ICISA 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 424))

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Abstract

In this paper, we come up with a bottom-up saliency algorithm that both consider the background and foreground cues. First, we compute the coarse saliency map by manifold ranking on a graph using partly image boundaries which consider as background prior. In this step, we just select left and top sides as background seeds. Second, bi-segment the preliminary saliency map to extract foreground information. Third, we utilize Markov absorption probabilities to highlight objects against the background. Results on public datasets show that our proposed method achieve fabulous performance.

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Acknowledgement

The research was partly supported by the program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning, USST incubation project (15HJPY-MS02), National Natural Science Foundation of China (No. U1304616, No. 61502220).

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Authors and Affiliations

  1. Shanghai Key Lab of Modern Optical Systems, University of Shanghai for Science and Technology, Shanghai, People’s Republic of China

    Xiao Lin, Zhixun Yan & Linhua Jiang

  2. CCSR, Stanford University, 269 Campus Drive, Stanford, California, 94305, USA

    Linhua Jiang

  3. The College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai, People’s Republic of China

    Xiao Lin

Authors
  1. Xiao Lin
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  2. Zhixun Yan
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  3. Linhua Jiang
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Corresponding author

Correspondence to Linhua Jiang .

Editor information

Editors and Affiliations

  1. Kyonggi University, Seongnam-si, Gyeonggi, Korea (Republic of)

    Kuinam Kim

  2. modelizeIT Inc., CEO and NYU , Stony Brook, New York, USA

    Nikolai Joukov

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© 2017 Springer Nature Singapore Pte Ltd.

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Lin, X., Yan, Z., Jiang, L. (2017). Saliency Detection via Foreground and Background Seeds. In: Kim, K., Joukov, N. (eds) Information Science and Applications 2017. ICISA 2017. Lecture Notes in Electrical Engineering, vol 424. Springer, Singapore. https://doi.org/10.1007/978-981-10-4154-9_18

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  • DOI: https://doi.org/10.1007/978-981-10-4154-9_18

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-4153-2

  • Online ISBN: 978-981-10-4154-9

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