Search results for key=FSN1995 : 1 match found.

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

1995

@article{FSN1995,
	vgclass =	{refpap},
	vgproject =	{cbir},
	author =	{Myron Flickner and Harpreet Sawhney and Wayne Niblack and
	Jonathan Ashley and Qian Huang and Byron Dom and Monika Gorkani and Jim
	Hafner and Denis Lee and Dragutin Petkovic and David Steele and Peter
	Yanker},
	title =	{Query by Image and Video Content: The {QBIC} System},
	journal =	{IEEE Computer},
	volume =	{28},
	number =	{9},
	pages =	{23--32},
	month =	{September},
	year =	{1995},
	url =	{http://ieeexplore.ieee.org/iel1/2/9181/00410146.pdf?isNumber=9181&prod=JNL&arnumber=410146&arNumber=410146&arSt=23&ared=32&arAuthor=Flickner%2C+M.%3B+Sawhney%2C+H.%3B+Niblack%2C+W.%3B+Ashley%2C+J.%3B+Qian+Huang%3B+Dom%2C+B.%3B+Gorkani%2C+M.%3B+Hafner%2C+J.%3B+Lee%2C+D.%3B+Petkovic%2C+D.%3B+Steele%2C+D.%3B+Yanker%2C+P.},
	abstract =	{Advances in scanning, networking, compression and video
	technology -- and the proliferation of multimedia computers -- have led
	to the generation of large on-line collections of images and videos.
	These collections have created a need for new methods to locate
	specific images or video clips. The Query by Image Content (QBIC)
	project is studying methods to extend and complement text-based
	retrievals by querying and retrieving images and videos by content.

	Queries can be performed using attributes such as colors, textures,
	shapes, and object position. Video-specific queries include those on
	camera motion parameters like zoom, pan, and object motion.

	The project has resulted in a prototype system with two major steps:
	database population and query. In population, methods identify objects
	in still images, segment videos into short sequences called shots, and
	compute features describing color, texture, shape, position, or motion
	information.  In database query, images and shots can be retrieved by
	example (``Show me images similar to this image'') or by selecting
	properties from pickers such as a color wheel, a sketched shape, a list
	of camera motions, or a combination of these.

	Key QBIC technical issues include a visual query language and a
	graphical user interface that lets users form a query by painting,
	sketching, or selecting graphical elements. Key also are indexing
	techniques for high-dimensional features describing image and video
	content, automatic segmentation techniques for images (to identify
	interesting objects), and videos (to identify shots and interesting
	moving and static objects), and similarity retrieval (to match human
	perception).

	QBIC technology has moved into the Multimedia and Digital Library
	commercial IBM products.},
}