Refereed full papers (journals, book chapters, international conferences)

1996

@inproceedings{WhJ1996a,
	vgclass =	{refpap},
	vgproject =	{cbir},
	author =	{David A. White and Ramesh Jain},
	title =	{Similarity indexing: algorithms and performance},
	editor =	{Ishwar K. Sethi and Ramesh C. Jain},
	booktitle =	{Storage and Retrieval for Still Image and Video Databases
	IV},
	volume =	{2670},
	series =	{SPIE Proceedings},
	pages =	{62--73},
	month =	{March},
	year =	{1996},
	abstract =	{Efficient indexing support is essential to allow
	content-based image and video databases using similarity-based
	retrieval to scale to large databases (tens of thousands up to millions
	of images).  In this paper, we take an in depth look at this problem.
	One of the major difficulties in solving this problem is the high
	dimension (6-100) of the feature vectors that are used to represent
	objects. We provide an overview of the work in computational geometry
	on this problem and highlight the results we found are most useful in
	practice, including the use of approximate nearest neighbor algorithms.
	We also present a variant of the optimized k-d tree we call the VAM k-d
	tree, and provide algorithms to create an optimized R-tree we call the
	VAMSplit R-tree. We found that the VAMSplit R-tree provided better
	overall performance than all competing structures we tested for main
	memory and secondary memory applications.  We observed large
	improvements in performance relative to the R*-tree and SS-tree in
	secondary memory applications, and modest improvements relative to
	optimized k-d tree variants.},
}