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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.
Date of Conference: 21-23 Sept. 2012