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SIGMOD '86 Proceedings of the 1986 ACM SIGMOD international conference on Management of data
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Analysis of the clustering properties of Hilbert space-filling curve
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STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
ACM Computing Surveys (CSUR)
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VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
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Analysis of Multi-Dimensional Space-Filling Curves
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Content-Based Retrieval of Images for Cultural Institutions Using Local Descriptors
GMAI '06 Proceedings of the conference on Geometric Modeling and Imaging: New Trends
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Nearest-Neighbor Methods in Learning and Vision: Theory and Practice (Neural Information Processing)
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ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
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IEEE Transactions on Computers
IEEE Transactions on Pattern Analysis and Machine Intelligence
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ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
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Computer Vision and Image Understanding
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In this paper we address the subject of large multimedia database indexing for content-based retrieval. We introduce multicurves, a new scheme for indexing high-dimensional descriptors. This technique, based on the simultaneous use of moderate-dimensional space-filling curves, has as main advantages the ability to handle high-dimensional data (100 dimensions and over), to allow the easy maintenance of the indexes (inclusion and deletion of data), and to adapt well to secondary storage, thus providing scalability to huge databases (millions, or even thousands of millions of descriptors). We use multicurves to perform the approximate k nearest neighbors search with a very good compromise between precision and speed. The evaluation of multicurves, carried out on large databases, demonstrates that the strategy compares well to other up-to-date k nearest neighbor search strategies. We also test multicurves on the real-world application of image identification for cultural institutions. In this application, which requires the fast search of a large amount of local descriptors, multicurves allows a dramatic speed-up in comparison to the brute-force strategy of sequential search, without any noticeable precision loss.