Fast indexing method for multidimensional nearest-neighbor search

John A. Shepherd; Xiaoming Zhu; Nimrod Megiddo

doi:10.1117/12.333854

17 December 1998 Fast indexing method for multidimensional nearest-neighbor search

John A. Shepherd, Xiaoming Zhu, Nimrod Megiddo

Proceedings Volume 3656, Storage and Retrieval for Image and Video Databases VII; (1998) https://doi.org/10.1117/12.333854
Event: Electronic Imaging '99, 1999, San Jose, CA, United States

Abstract

This paper describes a snapshot of work in progress on the development of an efficient file-access method for similarity searching in high-dimensional vector spaces. This method has applications in image databases, where images are accessed via high-dimensional feature vectors, as well as other areas. The technique is based on using a collection of space-filling curves, as an auxiliary indexing structure. Initial performance analyses suggest that the method works as efficiently in moderately high-dimensional spaces (256 dimensions), with tolerable storage and execution-time overhead.

Citation Download Citation

John A. Shepherd, Xiaoming Zhu, and Nimrod Megiddo "Fast indexing method for multidimensional nearest-neighbor search", Proc. SPIE 3656, Storage and Retrieval for Image and Video Databases VII, (17 December 1998); https://doi.org/10.1117/12.333854

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