A Multilayer Backpropagation Saliency Detection Algorithm Based on Depth Mining

被引：17

作者：

Zhu, Chunbiao ^{[1
]}

Li, Ge ^{[1
,2
]}

Guo, Xiaoqiang

Wang, Wenmin ^{[1
]}

Wang, Ronggang ^{[1
]}

机构：

[1] Peking Univ, Shenzhen Grad Sch, Sch Elect & Comp Engn, Shenzhen, Peoples R China

[2] SAPPRFT, Acad Broadcasting Sci, Beijing, Peoples R China

来源：

COMPUTER ANALYSIS OF IMAGES AND PATTERNS: 17TH INTERNATIONAL CONFERENCE, CAIP 2017, PT II | 2017年 / 10425卷

基金：

美国国家科学基金会;

关键词：

Saliency detection; Depth cue; Depth mining; Multilayer; Backpropagation; OBJECT DETECTION;

D O I：

10.1007/978-3-319-64698-5_2

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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 back-propagation 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.

引用

页码：14 / 23

页数：10

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