RGB-‘D’ Saliency Detection With Pseudo Depth
Xiaolin Xiao1; Yicong Zhou1; Yue-Jiao Gong2,3
Source PublicationIEEE Transactions on Image Processing
Volume28Issue:5Pages:2126 - 2139

Recent studies have shown the effectiveness of using depth information in salient object detection. However, the most commonly seen images so far are still RGB images that do not contain the depth data. Meanwhile, the human brain can extract the geometric model of a scene from an RGB-only image and hence provides a 3D perception of the scene. Inspired by this observation, we propose a new concept named RGB-‘D’ saliency detection, which derives pseudo depth from the RGB images and then performs 3D saliency detection. The pseudo depth can be utilized as image features, prior knowledge, an additional image channel, or independent depth-induced models to boost the performance of traditional RGB saliency models. As an illustration, we develop a new salient object detection algorithm that uses the pseudo depth to derive a depth-driven background prior and a depth contrast feature. Extensive experiments on several standard databases validate the promising performance of the proposed algorithm. In addition, we also adapt two supervised RGB saliency models to our RGB-‘D’ saliency framework for performance enhancement. The results further demonstrate the generalization ability of the proposed RGB-‘D’ saliency framework

KeywordRgb-‘d’ Saliency Pseudo Depth Salient Object Detection
Indexed BySCIE
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000456542000003
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Cited Times [WOS]:12   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Corresponding AuthorXiaolin Xiao; Yicong Zhou; Yue-Jiao Gong
Affiliation1.Department of Computer and Information Science, University of Macau, Macau 999078, China
2.South China Univ Technol, Sch Comp Sci & Engn, Guangzhou 510006, Guangdong, Peoples R China
3.South China Univ Technol, Guangdong Prov Key Lab Computat Intelligence & Cy, Guangzhou 510006, Guangdong, Peoples R China
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Xiaolin Xiao,Yicong Zhou,Yue-Jiao Gong. RGB-‘D’ Saliency Detection With Pseudo Depth[J]. IEEE Transactions on Image Processing,2018,28(5):2126 - 2139.
APA Xiaolin Xiao,Yicong Zhou,&Yue-Jiao Gong.(2018).RGB-‘D’ Saliency Detection With Pseudo Depth.IEEE Transactions on Image Processing,28(5),2126 - 2139.
MLA Xiaolin Xiao,et al."RGB-‘D’ Saliency Detection With Pseudo Depth".IEEE Transactions on Image Processing 28.5(2018):2126 - 2139.
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