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Saliency detection using multiple low-level priors and a propagation mechanism

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Abstract

The majority of existing methods for saliency detection based on low-level features failed to uniformly highlight the salient-object regions. In order to improve the accuracy and consistency of generated saliency maps, we propose a novel and efficient framework by combining low-level saliency priors and local similarity cues for image saliency detection. Firstly, we construct a multiple low-level prior map using location prior, color prior and background prior. Then, the prior maps employ a propagation mechanism based on Cellular Automata to enforce relevance of similar regions as a local similarity cue. Finally, a principle refinement framework by integrating multi-level prior maps and local similarity cue map are used to obtain an ultimate high-quality saliency map. Extensive experiments on publicly available datasets show that our designed approach is capable of producing accurate saliency maps compared with those generated results by the state-of-the-art saliency-detection methods.

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Acknowledgements

We would like to thank Prof. Hui Yu in the School of Creative Technologies, University of Portsmouth, for providing technical editing and proofreading of the manuscript.

This work was supported by National Natural Science Foundation of China (NSFC) (61601427, 61602229, 61771230); Royal Society – K. C. Wong International Fellow; Natural Science Foundation of Shandong Province (ZR2016FM40); Shandong Provincial Key Research and Development Program of China (NO. 2017CXGC0701); Fostering Project of Dominant Discipline and Talent Team of Shandong Province Higher Education Institutions.

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Authors and Affiliations

  1. School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, China

    Muwei Jian, Chaoran Cui & Xiushan Nie

  2. Department of Computer Science and Technology, Ocean University of China, Qingdao, China

    Muwei Jian, Jing Wang & Junyu Dong

  3. School of Software Engineering, Shandong University, Jinan, 250101, China

    Yilong Yin

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  1. Muwei Jian
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  2. Jing Wang
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  3. Junyu Dong
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  4. Chaoran Cui
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  5. Xiushan Nie
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  6. Yilong Yin
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Correspondence to Muwei Jian.

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Jian, M., Wang, J., Dong, J. et al. Saliency detection using multiple low-level priors and a propagation mechanism. Multimed Tools Appl 79, 33467–33482 (2020). https://doi.org/10.1007/s11042-019-07842-4

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  • DOI: https://doi.org/10.1007/s11042-019-07842-4

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