Search results for key=WYK1998 : 1 match found.

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

1998

@inproceedings{WYK1998,
	vgclass =	{refpap},
	vgproject =	{cbir},
	author =	{Xia Wan and Zijun Yang and Kuo, C.-C. Jay},
	title =	{Efficient interactive image retrieval with multiple seed
	images},
	editor =	{C.-C. Jay Kuo and Shih-Fu Chang and Sethuraman
	Panchanathan},
	booktitle =	{Multimedia Storage and Archiving Systems III (VV02)},
	address =	{Boston, Massachusetts, USA},
	volume =	{3527},
	series =	{SPIE Proceedings},
	pages =	{13--24},
	month =	{November},
	year =	{1998},
	note =	{(SPIE Symposium on Voice, Video and Data Communications)},
	abstract =	{An interactive query system based on multiple seed images
	is proposed in this work. With this proposed system, the query can be
	refined so that the meaning of similarity becomes clear along the query
	process. A particular way to achieve interactive query is implemented,
	i.e. adaptive filtering with multiple low-level indexing features based
	on user's feedback. The proposed query system consists of the following
	building blocks. First, browsing, image sketching and feature editing
	are employed for query formation input. The combination of the three
	methods provides high flexibility for users to get desired query
	images. In the system, images can also be selected from the candidate
	image set. By using a query set composed of multiple seed images
	instead of a single image, we can improve query performance with more
	accurate similarity information. Two key procedures, initial guess and
	further refinement, are utilized to achieve high efficient query. At
	the initial stage, we try to expand the candidate image set to include
	as many features as possible. In the refinement process, users are able
	to initiate a more complex filtering strategy by using the feedback.
	The relative weighting of different features is further decided.
	Extensive examples are used to illustrate the proposed interactive
	query process and the corresponding retrieval performance.},
}