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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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2018-01-01
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| Series: | IEEE Photonics Journal |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8534342/ |
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| Summary: | 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. |
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| ISSN: | 1943-0655 |