Human behaviour consistent relevance feedback model for image retrieval
Jing Liu; Zhiwei Li; Mingjing Li; Hanqing Lu; Songde Ma
2007
会议名称International Conference on Multimedia
会议录名称Proceedings of the 15th International Conference on Multimedia 2007
会议日期September 24-29, 2007
会议地点Augsburg, Germany
摘要Due to the well known semantic gap, content based image retrieval is a difficult problem. To bridge it, relevance feedback as an effective solution has been extensively studied in literatures. However, existing methods follow a single-line searching philosophy, which may lead to a local optimum in search space. To address the problem, we propose a human behavior consistent relevance feedback model for image retrieval in this paper. Simulating human behaviors, the proposed model enable the user to perform relevance feedback in three manners: Follow up, Go back, and Restart. Each manner is a way for the user to provide the system with his or her opinions about search results. The accumulated feedback information can be used to refine the user query and regulate the similarity metric. We adopt the graph ranking algorithm to model the retrieval process. Experiments conducted on standard Corel dataset and Pascal VOC 2006 dataset demonstrate the effectiveness of the proposed mechanism.
关键词Graph Ranking Image Retrieval Relevance Feedback
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/13454
专题模式识别国家重点实验室_图像与视频分析
通讯作者Jing Liu
推荐引用方式
GB/T 7714
Jing Liu,Zhiwei Li,Mingjing Li,et al. Human behaviour consistent relevance feedback model for image retrieval[C],2007.
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