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Exploiting color name space for salient object detection

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Abstract

In this paper, we will investigate the contribution of color names for the task of salient object detection. An input image is first converted to color name space, which is consisted of 11 probabilistic channels. By exploiting a surroundedness cue, we obtain a saliency map through a linear combination of a set of sequential attention maps. To overcome the limitation of only using the surroundedness cue, two global cues with respect to color names are invoked to guide the computation of a weighted saliency map. Finally, we integrate the above two saliency maps into a unified framework to generate the final result. In addition, an improved post-processing procedure is introduced to effectively suppress image backgrounds while uniformly highlight salient objects. Experimental results show that the proposed model produces more accurate saliency maps and performs well against twenty-one saliency models in terms of three evaluation metrics on three public data sets.

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Notes

  1. 1.

    http://lear.inrialpes.fr/people/vandeweijer/color_names.html

  2. 2.

    http://cs-people.bu.edu/jmzhang/BMS/BMS.html

  3. 3.

    http://www.escience.cn/people/jianli/DataBase.html

  4. 4.

    http://www.cse.cuhk.edu.hk/leojia/projects/hsaliency/

  5. 5.

    http://www.loujing.com/rpc-saliency/

  6. 6.

    http://www.escience.cn/people/chengong/Codes.html

  7. 7.

    http://cg.cs.tsinghua.edu.cn/people/~cmm/Saliency/Index.htm

  8. 8.

    http://mmcheng.net/msra10k/

  9. 9.

    http://mmcheng.net/salobjbenchmark/

  10. 10.

    http://research.microsoft.com/en-us/um/people/jiansun/SalientObject/salient_object.htm

  11. 11.

    http://ivrl.epfl.ch/supplementary_material/RK_CVPR09/

  12. 12.

    http://www.cse.cuhk.edu.hk/leojia/projects/hsaliency/dataset.html

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Acknowledgements

J. Lou is supported by the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province (No. 19KJB520022), the Science and Technology Special Project of CZIMT (No. 2019-ZXKJ-02), the Cultivation Object of Major Scientific Research Project of CZIMT (No. 2019ZDXM06), the Jiangsu Province Industry University Research Cooperation Project (No. FZ20190200), the Changzhou Key Laboratory of Industrial Internet and Data Intelligence (No. CM20183002), and the QingLan Project of Jiangsu Province (2018). The work of L. Chen, F. Xu, W. Zhu, and M. Ren is supported by the National Natural Science Foundation of China (Nos. 61231014 and 61727802). H. Wang is supported by the National Defense Pre-research Foundation of China (No. 9140A01060115BQ02002) and the National Natural Science Foundation of China (No. 61703209). Q. Xia is supported by the National Natural Science Foundation of China (No. 61403202) and the China Postdoctoral Science Foundation (No. 2014M561654). The authors thank Andong Wang and Haiyang Zhang for helpful discussions regarding this manuscript.

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Correspondence to Jing Lou or Mingwu Ren.

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Lou, J., Wang, H., Chen, L. et al. Exploiting color name space for salient object detection. Multimed Tools Appl (2019). https://doi.org/10.1007/s11042-019-07970-x

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Keywords

  • Saliency
  • Salient object detection
  • Figure-ground segregation
  • Surroundedness
  • Color names
  • Color name space