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Image saliency detection for multiple objects

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Abstract

Traditional saliency detection methods are designed only for a single salient object and cannot detect multiple salient objects in the image. This paper proposes a novel method for detecting multiple salient objects in the image, which is based on both objectness estimation method and superpixel segmentation method. The present study shows that the proposed method can correctly detect the salient regions for multiple objects and outperforms the other three state-of-the-art saliency detection methods.

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Acknowledgments

This research is supported by the National Natural Science Foundation of China (61662057, 61672143, U1435216), the Fundamental Research Funds for the Central Universities (N130404027, N151704004, N161602003), and Doctor Research Starting Foundation of Liaoning (No.20141011).

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Authors and Affiliations

  1. College of Software, Northeastern University, Shenyang, China

    Beilei Wang & Jie Song

  2. College of Information Science and Engineering, Northeastern University, Shenyang, China

    Lu Meng

Authors
  1. Beilei Wang
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  2. Lu Meng
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  3. Jie Song
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Correspondence to Lu Meng.

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Wang, B., Meng, L. & Song, J. Image saliency detection for multiple objects. Multimed Tools Appl 78, 5329–5343 (2019). https://doi.org/10.1007/s11042-018-5731-0

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  • DOI: https://doi.org/10.1007/s11042-018-5731-0

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