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Content-based image retrieval (CBIR) has attracted people's attention for many years, while the semantic gap and curse of dimensionality are still two open questions of CBIR. In this paper, we propose a new interactive image retrieval method based on locality-sensitive hashing (LSH) and support vector machine (SVM): LSH is adopted to overcome the curse of dimensionality and a SVM-based relevance feedback (RF) scheme is introduced to shorten the semantic gap. The experimental results show the effectiveness of the proposed method.
Published in:
Network Infrastructure and Digital Content (IC-NIDC), 2012 3rd IEEE International Conference on
Date of Conference: 21-23 Sept. 2012
- Page(s):
- 482 - 486
- Print ISBN:
- 978-1-4673-2201-0
- INSPEC Accession Number:
- 13264261
- Conference Location :
- Beijing
- Digital Object Identifier :
- 10.1109/ICNIDC.2012.6418800
- Product Type:
- Conference Publications
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