Enhanced nearest neighbour search on the R-tree
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Fast approximate nearest-neighbor search with k-nearest neighbor graph
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Fast search in Hamming space with multi-index hashing
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Supervised hashing with kernels
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Semi-Supervised Hashing for Large-Scale Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Nowadays, Nearest Neighbor Search becomes more and more important when facing the challenge of big data. Traditionally, to solve this problem, researchers mainly focus on building effective data structures such as hierarchical k-means tree or using hashing methods to accelerate the query process. In this paper, we propose a novel unified approximate nearest neighbor search scheme to combine the advantages of both the effective data structure and the fast Hamming distance computation in hashing methods. In this way, the searching procedure can be further accelerated. Computational complexity analysis and extensive experiments have demonstrated the effectiveness of our proposed scheme.