Issues Concerning Dimensionality and Similarity Search
 

Dept. of Electrical and Computer Engineering
University of California at Santa Barbara
Santa Barbara, CA 93106
Email: {jelena,sitaram,manj} @ece.ucsb.edu

Abstract

Effectiveness and efficiency are two important concerns
in using multimedia descriptors to search and access
database items. Both are affected by the dimensionality
of the descriptors. While higher dimensionality generally
increases effectiveness, it drastically reduces efficiency of
storage and searching. With regard to effectiveness, rele-vance
feedback is known to be a useful tool to squeeze in-formation
from a descriptor. However, not much has been
done toward enabling relevance feedback computation us-ing
high-dimensional descriptors over a large multimedia
dataset. In this context, we have developed new methods
that enable us to a) reduce the dimensionality of Gabor tex-ture
descriptors without losing on effectiveness, and b) per-form
fast nearest neighbor search based on the information
available during each iteration of a relevance feedback step.
Experimental results are presented on real datasets.