发明授权
US07113944B2 Relevance maximizing, iteration minimizing, relevance-feedback, content-based image retrieval (CBIR).
有权
相关性最大化，迭代最小化，相关性反馈，基于内容的图像检索（CBIR）。
- 专利标题： Relevance maximizing, iteration minimizing, relevance-feedback, content-based image retrieval (CBIR).
- 专利标题（中）： 相关性最大化，迭代最小化，相关性反馈，基于内容的图像检索（CBIR）。
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申请号： US11042456申请日： 2005-01-25
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公开(公告)号： US07113944B2公开(公告)日： 2006-09-26
- 发明人: Hong-Jiang Zhang , Zhong Su , Xingquan Zhu
- 申请人： Hong-Jiang Zhang , Zhong Su , Xingquan Zhu
- 申请人地址： US WA Redmond
- 专利权人： Microsoft Corporation
- 当前专利权人： Microsoft Corporation
- 当前专利权人地址： US WA Redmond
- 代理机构： Lee & Hayes, PLLC
- 主分类号： G06F17/30
- IPC分类号： G06F17/30
摘要：
An implementation of a technology, described herein, for relevance-feedback, content-based facilitating accurate and efficient image retrieval minimizes the number of iterations for user feedback regarding the semantic relevance of exemplary images while maximizing the resulting relevance of each iteration. One technique for accomplishing this is to use a Bayesian classifier to treat positive and negative feedback examples with different strategies. In addition, query refinement techniques are applied to pinpoint the users' intended queries with respect to their feedbacks. These techniques further enhance the accuracy and usability of relevance feedback. This abstract itself is not intended to limit the scope of this patent. The scope of the present invention is pointed out in the appending claims.