A Multilayer Backpropagation Saliency Detection Algorithm Based on Depth Mining

• Published in: Computer Analysis of Images and Patterns Vol. 10425; pp. 14 - 23
• Main Authors: Zhu, Chunbiao, Li, Ge, Guo, Xiaoqiang, Wang, Wenmin, Wang, Ronggang
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2017; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Backpropagation; Depth cue; Depth mining; Multilayer; Saliency detection
• ISBN: 3319646974; 9783319646978
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-64698-5_2

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.