Saliency detection with bilateral absorbing markov chain guided by depth information

doi:10.3390/s21030838

CORC > 长春光学精密机械与物理研究所 > 中国科学院长春光学精密机械与物理研究所

	Saliency detection with bilateral absorbing markov chain guided by depth information
	J. Wu; G. Han; P. Liu; H. Yang; H. Luo and Q. Li
刊名	Sensors (Switzerland)
	2021
卷号	21 期号:3 页码:1-23
ISSN号	14248220
DOI	10.3390/s21030838
英文摘要	The effectiveness of depth information in saliency detection has been fully proved. How-ever, it is still worth exploring how to utilize the depth information more efficiently. Erroneous depth information may cause detection failure, while non-salient objects may be closer to the camera which also leads to erroneously emphasis on non-salient regions. Moreover, most of the existing RGB-D saliency detection models have poor robustness when the salient object touches the image boundaries. To mitigate these problems, we propose a multi-stage saliency detection model with the bilateral absorbing Markov chain guided by depth information. The proposed model progressively extracts the saliency cues with three level (low-, mid-, and high-level) stages. First, we generate low-level saliency cues by explicitly combining color and depth information. Then, we design a bilateral absorbing Markov chain to calculate mid-level saliency maps. In mid-level, to suppress boundary touch problem, we present the background seed screening mechanism (BSSM) for improving the construction of the two-layer sparse graph and better selecting background-based absorbing nodes. Furthermore, the cross-modal multi-graph learning model (CMLM) is designed to fully explore the intrinsic complementary relationship between color and depth information. Finally, to obtain a more highlighted and homogeneous saliency map in high-level, we structure a depth-guided optimization module which combines cellular automata and suppression-enhancement function pair. This optimization module refines the saliency map in color space and depth space, respectively. Comprehensive experiments on three challenging benchmark datasets demonstrate the effectiveness of our proposed method both qualitatively and quantitatively. 2021 by the authors. Licensee MDPI, Basel, Switzerland.
URL标识	查看原文
内容类型	期刊论文
源URL	[http://ir.ciomp.ac.cn/handle/181722/65608]
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	J. Wu,G. Han,P. Liu,et al. Saliency detection with bilateral absorbing markov chain guided by depth information[J]. Sensors (Switzerland),2021,21(3):1-23.
APA	J. Wu,G. Han,P. Liu,H. Yang,&H. Luo and Q. Li.(2021).Saliency detection with bilateral absorbing markov chain guided by depth information.Sensors (Switzerland),21(3),1-23.
MLA	J. Wu,et al."Saliency detection with bilateral absorbing markov chain guided by depth information".Sensors (Switzerland) 21.3(2021):1-23.