Unsupervised Salient Object Detection by Aggregating Multi-Level Cues
In this paper, we present a novel method to detect salient object based on multi-level cues. First, a proposal processing scheme is developed by various object-level saliency cues to generate an initial saliency map. For the sake of more accurate object boundaries, a two-stage optimization mechanism...
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| Format: | Article |
| Language: | English |
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IEEE
2018-01-01
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| Series: | IEEE Photonics Journal |
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| Online Access: | https://ieeexplore.ieee.org/document/8534342/ |
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| author | Chenxing Xia Hanling Zhang |
| author_facet | Chenxing Xia Hanling Zhang |
| author_sort | Chenxing Xia |
| collection | DOAJ |
| description | In this paper, we present a novel method to detect salient object based on multi-level cues. First, a proposal processing scheme is developed by various object-level saliency cues to generate an initial saliency map. For the sake of more accurate object boundaries, a two-stage optimization mechanism is then proposed upon superpixel-level. Finally, the superpixel-level saliency map is further improved to construct the final saliency map by applying superpixel-to-pixel mapping. 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. |
| format | Article |
| id | doaj-art-0e3af6eb5a7e41709f4aeef2ef4c8ec5 |
| institution | OA Journals |
| issn | 1943-0655 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Photonics Journal |
| spelling | doaj-art-0e3af6eb5a7e41709f4aeef2ef4c8ec52025-08-20T02:38:03ZengIEEEIEEE Photonics Journal1943-06552018-01-0110611110.1109/JPHOT.2018.28812718534342Unsupervised Salient Object Detection by Aggregating Multi-Level CuesChenxing Xia0Hanling Zhang1https://orcid.org/0000-0001-5954-1424College of Computer Science and Electronic Engineering, Hunan University, Changsha, ChinaCollege of Computer Science and Electronic Engineering, Hunan University, Changsha, ChinaIn this paper, we present a novel method to detect salient object based on multi-level cues. First, a proposal processing scheme is developed by various object-level saliency cues to generate an initial saliency map. For the sake of more accurate object boundaries, a two-stage optimization mechanism is then proposed upon superpixel-level. Finally, the superpixel-level saliency map is further improved to construct the final saliency map by applying superpixel-to-pixel mapping. 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.https://ieeexplore.ieee.org/document/8534342/Saliency detectionmulti-level cuesobject proposals. |
| spellingShingle | Chenxing Xia Hanling Zhang Unsupervised Salient Object Detection by Aggregating Multi-Level Cues IEEE Photonics Journal Saliency detection multi-level cues object proposals. |
| title | Unsupervised Salient Object Detection by Aggregating Multi-Level Cues |
| title_full | Unsupervised Salient Object Detection by Aggregating Multi-Level Cues |
| title_fullStr | Unsupervised Salient Object Detection by Aggregating Multi-Level Cues |
| title_full_unstemmed | Unsupervised Salient Object Detection by Aggregating Multi-Level Cues |
| title_short | Unsupervised Salient Object Detection by Aggregating Multi-Level Cues |
| title_sort | unsupervised salient object detection by aggregating multi level cues |
| topic | Saliency detection multi-level cues object proposals. |
| url | https://ieeexplore.ieee.org/document/8534342/ |
| work_keys_str_mv | AT chenxingxia unsupervisedsalientobjectdetectionbyaggregatingmultilevelcues AT hanlingzhang unsupervisedsalientobjectdetectionbyaggregatingmultilevelcues |