PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Representing images with χ2 distance based histograms of SIFT descriptors
Jorma Laaksonen and Ville Viitaniemi
In: ICANN 2009, Limassol, Cyprus(2009).

Abstract

Histograms of local descriptors such as SIFT have proven to be powerful representations of image content. Often the histograms are formed using a clustering algorithm that compares the SIFT descriptors with the Euclidean distance. In this paper we experimentally investigate the usefulness of basing the comparisons of the SIFT descriptors on the χ2 distance measure instead. The modified approach results in improved image category detection performance when it is incorporated into a Bag-of-Visual-Words type category detection system.

EPrint Type:Conference or Workshop Item (Oral)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:6605
Deposited By:Ville Viitaniemi
Deposited On:08 March 2010