Cart (Loading....) | Create Account
Close category search window
 

Non-uniform partition strategies for indexing high-dimensional data with different distributions

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Wang, B. ; Dept. of Comput. Sci., Essex Univ., Colchester, UK ; Qiang Gan

Efficient high-dimensional data indexing algorithms are crucial for image retrieval in large datasets. One of the state-of-the-art indexing methods is vector approximation file (VA-file), which indexes high-dimensional data by filtering feature vectors so that only a small fraction of them are visited in the search process. The VA-file uses a partition strategy that divides the data space on every dimension to make each partition equally full and assigns a same number of bits to each dimension. However, the strategy is not efficient to image datasets where the number of different vector components (granularity) in each dimension is largely diverse. The first two partition strategies are implemented in a practical way according to the description from the original VA-file method. The other two nonuniform partition strategies are proposed to resolve the problems of reduplicate coordinates and uniform bits assignment for each dimension, which assign more bits to represent dimensions with more vector components. Experimental results have shown that these strategies largely improve the performance of the VA-file for nonuniform datasets in terms of query time and filtering efficiency.

Published in:

Multimedia Software Engineering, 2003. Proceedings. Fifth International Symposium on

Date of Conference:

10-12 Dec. 2003

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.