Robust saliency detection via corner information and an energy function
In this study, the authors propose a distinctive bottom‐up visual saliency detection algorithm based on a new background prior and a new reinforcement. Inspired by genetic algorithm, the final map is obtained with three steps. First of all, the authors construct a background‐based saliency map by ma...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-09-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/iet-cvi.2016.0492 |
| _version_ | 1797684196993400832 |
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| author | Hanling Zhang Chenxing Xia Xiuju Gao |
| author_facet | Hanling Zhang Chenxing Xia Xiuju Gao |
| author_sort | Hanling Zhang |
| collection | DOAJ |
| description | In this study, the authors propose a distinctive bottom‐up visual saliency detection algorithm based on a new background prior and a new reinforcement. Inspired by genetic algorithm, the final map is obtained with three steps. First of all, the authors construct a background‐based saliency map by manifold ranking via superior image corners selected by convex‐hull as background prior, which is different from most of the existing background prior‐based methods treated all image boundaries as background. Then, a better result is obtained by ranking the relevance of the image elements with foreground seeds extracted from the preliminary saliency map. Furthermore, a novel optimisation framework is introduced with the intention of refining the map, which integrates an energy function with a guided filter. Experimental results on three public datasets indicate that the proposed method performs favourably against the state‐of‐the‐art algorithms. |
| first_indexed | 2024-03-12T00:26:08Z |
| format | Article |
| id | doaj.art-4cff5edaa5d1477c836f562c322d6489 |
| institution | Directory Open Access Journal |
| issn | 1751-9632 1751-9640 |
| language | English |
| last_indexed | 2024-03-12T00:26:08Z |
| publishDate | 2017-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Computer Vision |
| spelling | doaj.art-4cff5edaa5d1477c836f562c322d64892023-09-15T10:36:02ZengWileyIET Computer Vision1751-96321751-96402017-09-0111637938810.1049/iet-cvi.2016.0492Robust saliency detection via corner information and an energy functionHanling Zhang0Chenxing Xia1Xiuju Gao2College of Computer Science and Electronic EngineeringHunan UniversityChangsha410082People's Republic of ChinaCollege of Computer Science and Electronic EngineeringHunan UniversityChangsha410082People's Republic of ChinaCollege of Computer Science and Electronic EngineeringHunan UniversityChangsha410082People's Republic of ChinaIn this study, the authors propose a distinctive bottom‐up visual saliency detection algorithm based on a new background prior and a new reinforcement. Inspired by genetic algorithm, the final map is obtained with three steps. First of all, the authors construct a background‐based saliency map by manifold ranking via superior image corners selected by convex‐hull as background prior, which is different from most of the existing background prior‐based methods treated all image boundaries as background. Then, a better result is obtained by ranking the relevance of the image elements with foreground seeds extracted from the preliminary saliency map. Furthermore, a novel optimisation framework is introduced with the intention of refining the map, which integrates an energy function with a guided filter. Experimental results on three public datasets indicate that the proposed method performs favourably against the state‐of‐the‐art algorithms.https://doi.org/10.1049/iet-cvi.2016.0492robust saliency detectioncorner informationenergy functionvisual saliency detection algorithmgenetic algorithmmanifold ranking |
| spellingShingle | Hanling Zhang Chenxing Xia Xiuju Gao Robust saliency detection via corner information and an energy function IET Computer Vision robust saliency detection corner information energy function visual saliency detection algorithm genetic algorithm manifold ranking |
| title | Robust saliency detection via corner information and an energy function |
| title_full | Robust saliency detection via corner information and an energy function |
| title_fullStr | Robust saliency detection via corner information and an energy function |
| title_full_unstemmed | Robust saliency detection via corner information and an energy function |
| title_short | Robust saliency detection via corner information and an energy function |
| title_sort | robust saliency detection via corner information and an energy function |
| topic | robust saliency detection corner information energy function visual saliency detection algorithm genetic algorithm manifold ranking |
| url | https://doi.org/10.1049/iet-cvi.2016.0492 |
| work_keys_str_mv | AT hanlingzhang robustsaliencydetectionviacornerinformationandanenergyfunction AT chenxingxia robustsaliencydetectionviacornerinformationandanenergyfunction AT xiujugao robustsaliencydetectionviacornerinformationandanenergyfunction |