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

1998

@article{RHO1998,
	vgclass =	{refpap},
	vgproject =	{cbir},
	author =	{Yong Rui and Thomas S. Huang and Michael Ortega and
	Sharad Mehrotra},
	title =	{Relevance Feedback: A Power Tool in Interactive
	Content-Based Image Retrieval},
	journal =	{IEEE Transactions on Circuits and Systems for Video Technology},
	volume =	{8},
	number =	{5},
	pages =	{644--655},
	month =	{September},
	year =	{1998},
	url =	{http://www-db.ics.uci.edu/pages/publications/1998/TR-MARS-98-10.ps},
	url1 =	{http://www.research.microsoft.com/~yongrui/ps/csvt98.ps.Z},
	abstract =	{Content-Based Image Retrieval (CBIR) has become one of the
	most active research areas in the past few years. Many visual feature
	representations have been explored and many systems built. While these
	research efforts establish the basis of CBIR, the usefulness of the
	proposed approaches is limited. Specifically, these efforts have
	relatively ignored two distinct characteristics of CBIR systems: (1)
	the gap between high level concepts and low level features; (2)
	subjectivity of human perception of visual content.  This paper
	proposes a relevance feedback based interactive retrieval approach,
	which effectively takes into account the above two characteristics in
	CBIR. During the retrieval process, the user's high level query and
	perception subjectivity are captured by dynamically updated weights
	based on the user's feedback. The experimental results over more than
	70,000 images show that the proposed approach greatly reduces the
	user's effort of composing a query and captures the user's information
	need more precisely.},
}