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

1997

@inproceedings{CBG1997,
	vgclass =	{refpap},
	vgproject =	{cbir},
	author =	{Chad Carson and Serge Belongie and Hayit Greenspan and
	Jitendra Malik},
	title =	{Region-Based Image Querying},
	booktitle =	{Proceedings of the 1997 IEEE Conference on Computer Vision and Pattern Recognition (CVPR'97)},
	address =	{San Juan, Puerto Rico},
	pages =	{42--49},
	month =	{June},
	year =	{1997},
	note =	{(Workshop on Content-Based Access of Image and Video
	Libraries)},
	url =	{http://elib.cs.berkeley.edu/carson/papers/cvpr97.html},
	url1 =	{http://elib.cs.berkeley.edu/carson/papers/cvpr97.ps.gz},
	url2 =	{http://elib.cs.berkeley.edu/carson/papers/cvpr97.pdf},
	abstract =	{Retrieving images from large and varied collections using
	image content as a key is a challenging and important problem. In this
	paper we present a new image representation which provides a
	transformation from the raw pixel data to a small set of localized
	coherent regions in color and texture space. This so-called
	``blobworld'' representation is based on segmentation using the
	Expectation-Maximization algorithm on combined color and texture
	features. The texture features we use for the segmentation arise from a
	new approach to texture description and scale selection.

	We describe a system that uses the blobworld representation to retrieve
	images. An important and unique aspect of the system is that, in the
	context of similarity-based querying, the user is allowed to view the
	internal representation of the submitted image and the query results.
	Similar systems do not offer the user this view into the workings of
	the system; consequently, the outcome of many queries on these systems
	can be quite inexplicable, despite the availability of knobs for
	adjusting the similarity metric.},
}