Fast Multivariate Ordinal Type Histogram Matching

Authors:
Sung-Hyuk Cha
Affiliations:
Department of Computer Science, Pace University, Pleasantville NY 10570
Venue:
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Year:
2008

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Abstract

When patterns are represented as histograms, the earth mover's distance , EMD has been considered an excellent metric between two distributions. EMD is formulated as the transportation problem which is a hard optimization problem. In similarity based pattern retrieval problems, computing EMD s for all histograms in the database against a query histogram would take too long time for users to wait for the output. Hence, the candidate selection technique is presented to speed up the EMD based multivariate ordinal type histogram retrieval problem. It guarantees to find all similar histograms while achieving significant speed up. Theoretical relationships between other metrics for multivariate histograms and their usages are presented as well.