Favorite object extraction using web images

Fanman Meng, Bing Luo, Chao Huang, Liangzhi Tang, Bing Zeng, Nini Rao

Research output: Chapter in Book/Conference Proceeding/ReportConference Paper published in a bookpeer-review

1 Citation (Scopus)

Abstract

In this paper, we propose a framework to discover and segment favorite object from the natural images. The main idea is to first generate the shape based common template of the favorite object using the images collected from the web. Then, the common template is used to extract the favorite object from the original images. In the common template generation, co-segmentation is used to provide the initial segments. The median graph theory is employed to construct the common template. We also propose a new shape descriptor namely directional shape representation to handle shape variations. We test our method on the images collected from image datasets and web. Experimental results demonstrate the effectiveness of the proposed method.

Original languageEnglish
Title of host publication2014 IEEE International Symposium on Circuits and Systems, ISCAS 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages349-352
Number of pages4
ISBN (Print)9781479934324
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event2014 IEEE International Symposium on Circuits and Systems, ISCAS 2014 - Melbourne, VIC, Australia
Duration: 1 Jun 20145 Jun 2014

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)0271-4310

Conference

Conference2014 IEEE International Symposium on Circuits and Systems, ISCAS 2014
Country/TerritoryAustralia
CityMelbourne, VIC
Period1/06/145/06/14

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