[1]ZHAO Runxia,JIAN Muwei,QI Qiang,et al.Saliency detection model based on the union of Object Proposals[J].CAAI Transactions on Intelligent Systems,2018,13(6):946-951.[doi:10.11992/tis.201801009]
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Saliency detection model based on the union of Object Proposals

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 13 Number of periods: 2018 6 Page number: 946-951 Column: 学术论文—机器学习 Public date: 2018-10-25
Title:
Saliency detection model based on the union of Object Proposals
Author(s):
ZHAO Runxia1;  JIAN Muwei1; 2;  QI Qiang1;  WANG Jing1;  WANG Ruihong1;  DONG Junyu1
1. College of Information Science and Engineering, Ocean University of China, Qingdao 266000, China;
2. School of Computer Science & Technology, Shandong University of Finance and Economics, Ji’nan 250014, China
Keywords:
saliency detection; Object Proposal; superpixels; texture; background map; global contrast; boundary connectivity; bottom-up
CLC:
TP391
DOI:
10.11992/tis.201801009
Abstract:
In saliency detection, current existing models usually produce results containing many background regions. To improve the performance, a novel saliency detection model is proposed based on the union of object proposals. The model first generates a series of object proposals from the input pictures, and then gets the background map by computing the union, and then obtains the initial saliency map by combining the texture and global contrast. Finally, the final saliency map is derived by restraining the initial saliency map with the obtained background map. Experimental results on the general MSRA1000 dataset demonstrate that the proposed saliency model performs well compared to the other five existing methods.
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Last Update: 2018-12-25

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