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EMR: Extended Manifold Ranking for Saliency Detection

  • Bo LiEmail author
  • Hang Gao
  • Han Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10262)

Abstract

A novel and outstanding saliency detection approach based on color features and background prior is proposed in this paper. Specifically, background prior is used in saliency detection widely, which considers the image boundaries as part of background. Then we propose an extended manifold ranking (EMR) algorithm to propagate the background prior to other image regions. Compared with GMR, EMR eliminates the negative effect of the initial assumption that non-boundary areas are all saliency regions. Furthermore, gradient boosting decision tree (GBDT) is introduced to refine the saliency map generated by EMR. The experimental results on three benchmark datasets demonstrate that our algorithm outperforms 10 state-of-the-art methods based on low-level features.

Keywords

Background prior Manifold ranking EMR GBDT 

Notes

Acknowledgement

This research was supported by the National Natural Science Foundation of China (Grant Nos. 11627802, 51678249), by the Science and Technology Projects of Guangdong (2013A011403003), and by the Science and Technology Projects of Guangzhou (201508010023).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of Electronic and Information EngineeringSouth China University of TechnologyGuangzhouChina

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