Search results for key=Squ1998 : 1 match found.

1998

• @techreport{Squ1998,
  	vgclass =	{report},
  	vgproject =	{viper,cbir},
  	author =	{David McG. Squire},
  	title =	{Generalization performance of factor analysis techniques
  	used for image database organization},
  	number =	{98.01},
  	institution =	{Computer Vision Group,  Computing Centre, University
  	of Geneva},
  	address =	{rue G\'{e}n\'{e}ral Dufour, 24, CH-1211 Gen\`{e}ve,
  	Switzerland},
  	month =	{January},
  	year =	{1998},
  	url =	{/publications/postscript/1998/VGTR98.01_Squire.pdf},
  	url1 =	{/publications/postscript/1998/VGTR98.01_Squire.ps.gz},
  	abstract =	{The goal of this paper is to evaluate the generalization
  	performance of a variety of factor analysis techniques in an image
  	database environment. Factor analysis techniques, such as Principal
  	Components Analysis, have been proposed as means of reducing the
  	dimensionality of the data stored in image retrieval systems. These
  	techniques compute a transformation which is applied to vectors of
  	image features to produce vectors of lower dimensionality which still
  	characterize the original data well. Computing such transformations for
  	very large numbers of images is computationally expensive, especially
  	if this calculation must be repeated each time new images are added to
  	the database. It is to be hoped, therefore, that a transformation
  	computed using a subset of all possible images will perform well when
  	applied to images not used in its derivation.  To evaluate this
  	generalization ability, we measure the agreement between partitionings
  	of image sets computed using such transformations with those produced
  	by human subjects.},
  }