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A Multilayer Backpropagation Saliency Detection Algorithm Based on Depth Mining

Conference paper
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Part of the Lecture Notes in Computer Science book series (LNCS, volume 10425)

Abstract

Saliency detection is an active topic in multimedia field. Several algorithms have been proposed in this field. Most previous works on saliency detection focus on 2D images. However, for some complex situations which contain multiple objects or complex background, they are not robust and their performances are not satisfied. Recently, 3D visual information supplies a powerful cue for saliency detection. In this paper, we propose a multilayer backpropagation saliency detection algorithm based on depth mining by which we exploit depth cue from four different layers of images. The evaluation of the proposed algorithm on two challenging datasets shows that our algorithm outperforms state-of-the-art.

Keywords

Saliency detection Depth cue Depth mining Multilayer Backpropagation 

Notes

Acknowledgments

This work was supported by the grant of National Science Foundation of China (No.U1611461), the grant of Science and Technology Planning Project of Guangdong Province, China (No.2014B090910001), the grant of Guangdong Province Projects of 2014B010117007 and the grant of Shenzhen Peacock Plan (No.20130408-183003656).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of Electronic and Computer EngineeringShenzhen Graduate School, Peking UniversityShenzhenChina
  2. 2.Academy of Broadcasting Science, SAPPRFTBeijingChina

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