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Saliency Detection by Multilevel Deep Pyramid Model
Joint Authors
Wang, Hai
Zhang, Yong
Cai, Yingfeng
Dai, Lei
Chen, Long
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-08-14
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Traditional salient object detection models are divided into several classes based on low-level features and contrast between pixels.
In this paper, we propose a model based on a multilevel deep pyramid (MLDP), which involves fusing multiple features on different levels.
Firstly, the MLDP uses the original image as the input for a VGG16 model to extract high-level features and form an initial saliency map.
Next, the MLDP further extracts high-level features to form a saliency map based on a deep pyramid.
Then, the MLDP obtains the salient map fused with superpixels by extracting low-level features.
After that, the MLDP applies background noise filtering to the saliency map fused with superpixels in order to filter out the interference of background noise and form a saliency map based on the foreground.
Lastly, the MLDP combines the saliency map fused with the superpixels with the saliency map based on the foreground, which results in the final saliency map.
The MLDP is not limited to low-level features while it fuses multiple features and achieves good results when extracting salient targets.
As can be seen in our experiment section, the MLDP is better than the other 7 state-of-the-art models across three different public saliency datasets.
Therefore, the MLDP has superiority and wide applicability in extraction of salient targets.
American Psychological Association (APA)
Wang, Hai& Dai, Lei& Cai, Yingfeng& Chen, Long& Zhang, Yong. 2018. Saliency Detection by Multilevel Deep Pyramid Model. Journal of Sensors،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1202169
Modern Language Association (MLA)
Wang, Hai…[et al.]. Saliency Detection by Multilevel Deep Pyramid Model. Journal of Sensors No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1202169
American Medical Association (AMA)
Wang, Hai& Dai, Lei& Cai, Yingfeng& Chen, Long& Zhang, Yong. Saliency Detection by Multilevel Deep Pyramid Model. Journal of Sensors. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1202169
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1202169