A novel graph structure for salient object detection based on divergence background and compact foreground Article Swipe
Chenxing Xia
,
Hanling Zhang
,
Keqin Li
·
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1711.11266
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1711.11266
In this paper, we propose an efficient and discriminative model for salient object detection. Our method is carried out in a stepwise mechanism based on both divergence background and compact foreground cues. In order to effectively enhance the distinction between nodes along object boundaries and the similarity among object regions, a graph is constructed by introducing the concept of virtual node. To remove incorrect outputs, a scheme for selecting background seeds and a method for generating compactness foreground regions are introduced, respectively. Different from prior methods, we calculate the saliency value of each node based on the relationship between the corresponding node and the virtual node. In order to achieve significant performance improvement consistently, we propose an Extended Manifold Ranking (EMR) algorithm, which subtly combines suppressed / active nodes and mid-level information. Extensive experimental results demonstrate that the proposed algorithm performs favorably against the state-of-art saliency detection methods in terms of different evaluation metrics on several benchmark datasets.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/1711.11266
- https://arxiv.org/pdf/1711.11266
- OA Status
- green
- Cited By
- 1
- References
- 9
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2772914069
All OpenAlex metadata
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- OpenAlex ID
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https://openalex.org/W2772914069Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.1711.11266Digital Object Identifier
- Title
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A novel graph structure for salient object detection based on divergence background and compact foregroundWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2017Year of publication
- Publication date
-
2017-11-30Full publication date if available
- Authors
-
Chenxing Xia, Hanling Zhang, Keqin LiList of authors in order
- Landing page
-
https://arxiv.org/abs/1711.11266Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/1711.11266Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/1711.11266Direct OA link when available
- Concepts
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Foreground detection, Computer science, Salient, Artificial intelligence, Graph, Computer vision, Divergence (linguistics), Object detection, Pattern recognition (psychology), Theoretical computer science, Linguistics, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2019: 1Per-year citation counts (last 5 years)
- References (count)
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9Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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