Saliency Detection via Background Seeds by Object Proposals

Muwei Jian, Runxia Zhao, Junyu Dong, Kin Man Lam

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

In the recent research of saliency detection, many graph-based algorithms are applied, which use the border of an image as a background query. This frequently leads to undesired errors and retrieval outputs when the boundaries of the salient objects concerned touch, or connect with, the image's border. In this paper, we propose a novel bottom-up saliency-detection algorithm to tackle and overcome the above issue. First, we utilize object proposals to collect the background seeds reliably. Then, the Extended Random Walk algorithm is adopted to propagate the prior background labels to the rest of the pixels in an image. Finally, we refine the saliency map by taking both the textural and structural information into consideration simultaneously. Experiments on publicly available data sets show that our proposed approach achieves competitive results against the state-of-the-art methods.

Original languageEnglish
Title of host publication2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1100-1105
Number of pages6
ISBN (Electronic)9789881476852
DOIs
Publication statusPublished - 12 Nov 2018
Event10th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Honolulu, United States
Duration: 12 Nov 201815 Nov 2018

Publication series

Name2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings

Conference

Conference10th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018
Country/TerritoryUnited States
CityHonolulu
Period12/11/1815/11/18

ASJC Scopus subject areas

  • Information Systems

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