NDLI: Subspace Clustering and Label Propagation for Active Feedback in Image Retrieval

Content Provider	IEEE Xplore Digital Library
Author	Tao Qin Tie-Yan Liu Xu-Dong Zhang Wei-Ying Ma Hong-Jiang Zhang
Copyright Year	2005
Description	Author affiliation: Tsinghua University (Tao Qin)
Abstract	In recent years, relevance feedback has been studied extensively as a way to improve performance of content-based image retrieval (CBIR). However, since users are usually unwilling to provide many feedbacks, the insufficiency of the training samples limited the success of relevance feedback. To tackle this problem, we propose two coupled algorithms: (i) overlapped subspace clustering to select representative images for users feedback; and (ii) multi-subspace label propagation to include unlabeled data in the training process. As these two algorithms are both working on sub feature spaces of the image database, they can not only deal with the insufficient training samples but also well capture the users attention during the retrieval process. Experimental results on a large database of general-purposed images demonstrated the high effectiveness of our proposed algorithms.
Starting Page	172
Ending Page	179
File Size	199525
Page Count	8
File Format	PDF
ISBN	0769521649
ISSN	15505502
DOI	10.1109/MMMC.2005.69
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-01-12
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feedback Image retrieval Clustering algorithms Support vector machines Asia Content based retrieval Image databases Partitioning algorithms Machine learning algorithms Support vector machine classification
Content Type	Text
Resource Type	Article

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