Shape-based image retrieval with relevance feedback

被引：0
|
作者：
Ma, LM [1 ]
Zhou, Q [1 ]
Chelberg, D [1 ]
Celenk, M [1 ]
机构：
[1] Ohio Univ, Stocker Ctr, Sch Elect Engn & Comp Sci, Athens, OH 45701 USA
来源：
2004 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXP (ICME), VOLS 1-3 | 2004年
关键词：
D O I：
10.1109/ICME.2004.1394316
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper proposes an adaptive frame work for shape-based image retrieval with relevance feedback. The motivation is to find an adjustable shape representation scheme that can account for feedback information. Relevance feedback is modeled as a dynamic eigenspace decomposition, and is used to classes the database into relevant and irrelevant groups with respect to the query. Eigenvectors of the sub-space are updated by optimizing a linear transform with respect to the J(3) class separability criterion. Experimental results show that the proposed approach can effectively capture a user's perceptual subjectivity.
引用
收藏
页码：779 / 782
页数：4
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