Web image organization and object discovery by actively creating visual clusters through crowdsourcing
In this paper, we propose to organize web images by actively creating visual clusters via crowd sourcing. We develop a two-phase framework to efficiently and effectively combine computers and a large number of human workers to build high quality visual clusters. The first phase partitions an image c...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/99351 http://hdl.handle.net/10220/12832 |
| _version_ | 1811686163622133760 |
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| author | Chen, Qi Wang, Gang Tan, Chew Lim |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Chen, Qi Wang, Gang Tan, Chew Lim |
| author_sort | Chen, Qi |
| collection | NTU |
| description | In this paper, we propose to organize web images by actively creating visual clusters via crowd sourcing. We develop a two-phase framework to efficiently and effectively combine computers and a large number of human workers to build high quality visual clusters. The first phase partitions an image collection into multiple clusters, the second phase refines each generated cluster independently. In both phases, informative images are selected by computers and manually labeled by the crowds to learn improved models. Our method can be naturally extended to discover object categories in a collection of image segments. Experimental results on several data sets demonstrate the promise of our developed approach on both web image organization and object discovery tasks. |
| first_indexed | 2024-10-01T04:56:03Z |
| format | Conference Paper |
| id | ntu-10356/99351 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:56:03Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/993512020-03-07T13:24:49Z Web image organization and object discovery by actively creating visual clusters through crowdsourcing Chen, Qi Wang, Gang Tan, Chew Lim School of Electrical and Electronic Engineering IEEE International Conference on Tools with Artificial Intelligence (24th : 2012 : Athens, Greece) DRNTU::Engineering::Electrical and electronic engineering In this paper, we propose to organize web images by actively creating visual clusters via crowd sourcing. We develop a two-phase framework to efficiently and effectively combine computers and a large number of human workers to build high quality visual clusters. The first phase partitions an image collection into multiple clusters, the second phase refines each generated cluster independently. In both phases, informative images are selected by computers and manually labeled by the crowds to learn improved models. Our method can be naturally extended to discover object categories in a collection of image segments. Experimental results on several data sets demonstrate the promise of our developed approach on both web image organization and object discovery tasks. 2013-08-02T02:56:34Z 2019-12-06T20:06:20Z 2013-08-02T02:56:34Z 2019-12-06T20:06:20Z 2012 2012 Conference Paper https://hdl.handle.net/10356/99351 http://hdl.handle.net/10220/12832 10.1109/ICTAI.2012.64 en |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering Chen, Qi Wang, Gang Tan, Chew Lim Web image organization and object discovery by actively creating visual clusters through crowdsourcing |
| title | Web image organization and object discovery by actively creating visual clusters through crowdsourcing |
| title_full | Web image organization and object discovery by actively creating visual clusters through crowdsourcing |
| title_fullStr | Web image organization and object discovery by actively creating visual clusters through crowdsourcing |
| title_full_unstemmed | Web image organization and object discovery by actively creating visual clusters through crowdsourcing |
| title_short | Web image organization and object discovery by actively creating visual clusters through crowdsourcing |
| title_sort | web image organization and object discovery by actively creating visual clusters through crowdsourcing |
| topic | DRNTU::Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/99351 http://hdl.handle.net/10220/12832 |
| work_keys_str_mv | AT chenqi webimageorganizationandobjectdiscoverybyactivelycreatingvisualclustersthroughcrowdsourcing AT wanggang webimageorganizationandobjectdiscoverybyactivelycreatingvisualclustersthroughcrowdsourcing AT tanchewlim webimageorganizationandobjectdiscoverybyactivelycreatingvisualclustersthroughcrowdsourcing |