Interpretation of users’ feedback via swarmed particles for content-based image retrieval
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- 作者：Yingying Zhua ; b ; Yingying.Zhu@utsa.edu" class="auth_mail" title="E-mail the corresponding author ; Jianmin Jianga ; jianmin.jiang@szu.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Wenlong Hana ; 970442195@qq.com" class="auth_mail" title="E-mail the corresponding author ; Ying Dingc ; dingying@cust.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Qi Tiana ; b ; qitian@cs.utsa.edu" class="auth_mail" title="E-mail the corresponding author
- 关键词：Relevance feedback ; User interactions ; Content-based image retrieval ; Particle swarm optimization
- 刊名：Information Sciences
- 出版年：2017
- 出版时间：1 January 2017
- 年：2017
- 卷：375
- 期：Complete
- 页码：246-257
- 全文大小：1533 K
文摘
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Interpretation of users feedback is independent of both the content features and relevance feedback schemes, and hence the proposed algorithm can be applicable to any content features and relevance feedback methods;
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The RF interpretation is followed by a group of swarmed particles, acting as multiple agents rather than a single query image in searching for the desirable images;
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The proposed RF interpretation and learning is exploited not only in reweighting the content similarity measurement, but also in regrouping the database images.