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Saliency Detection via Multi-view Synchronized Manifold Ranking

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Advances in Brain Inspired Cognitive Systems (BICS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10989))

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Abstract

Saliency detection is an important problem in computer vision. Recently, graph-based manifold ranking (GMR) has been successfully employed in image saliency detection problem. Traditional GMR involves two main ranking stages, i.e., ranking with background queries and ranking with foreground queries. However, these two ranking stages are conducted separately which obviously ignores the correlation between background and foreground queries. Also, traditional GMR uses a single graph which lacks of considering multi-view features. To overcome these problems, in this paper, we propose a new multi-view synchronized manifold ranking for saliency detection problem. Our method aims to perform background and foreground ranking simultaneously by exploiting multiple kinds of features and thus performs more robustly and discriminatively for saliency detection problem. Experimental results on three benchmark datasets demonstrate the effectiveness of the proposed saliency detection method.

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Acknowledgments

This work was supported by the National Nature Science Foundation of China (61602001, 61502006, 61402002); Natural Science Foundation of Anhui Higher Education Institutions of China (KJ2016A020, KJ2018A0023), Natural science foundation of Anhui Province (1508085QF127).

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Authors and Affiliations

  1. School of Computer Science and Technology, Anhui University, No. 111 Jiulong Road, Hefei, China

    Yuanyuan Guan, Bo Jiang, Yuan Zhang, Aihua Zheng, Dengdi Sun & Bin Luo

Authors
  1. Yuanyuan Guan
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  2. Bo Jiang
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  3. Yuan Zhang
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  4. Aihua Zheng
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  5. Dengdi Sun
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  6. Bin Luo
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Corresponding author

Correspondence to Bo Jiang .

Editor information

Editors and Affiliations

  1. University of Strathclyde, Glasgow, UK

    Jinchang Ren

  2. Edinburgh Napier University, Edinburgh, UK

    Amir Hussain

  3. Northwestern Polytechnical University, Xi’an, China

    Jiangbin Zheng

  4. Chinese Academy of Sciences, Beijing, China

    Cheng-Lin Liu

  5. Anhui University, Hefei, China

    Bin Luo

  6. Guangdong Polytechnic Normal University, Guangzhou, China

    Huimin Zhao

  7. Northwestern Polytechnical University, Xi’an, China

    Xinbo Zhao

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Guan, Y., Jiang, B., Zhang, Y., Zheng, A., Sun, D., Luo, B. (2018). Saliency Detection via Multi-view Synchronized Manifold Ranking. In: Ren, J., et al. Advances in Brain Inspired Cognitive Systems. BICS 2018. Lecture Notes in Computer Science(), vol 10989. Springer, Cham. https://doi.org/10.1007/978-3-030-00563-4_46

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  • DOI: https://doi.org/10.1007/978-3-030-00563-4_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00562-7

  • Online ISBN: 978-3-030-00563-4

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