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

1999

@inproceedings{HWF1999,
	vgclass =	{refpap},
	vgproject =	{cbir},
	author =	{Wey-Shiuan Hwang and John J. Weng and Ming Fang and Jianzhong Qian},
	title =	{A Fast Image Retrieval Algorithm with Automatically Extracted Discriminant Features},
	booktitle =	{IEEE Workshop on Content-based Access of Image and Video
	Libraries (CBAIVL'99)},
	address =	{Fort Collins, Colorado, USA},
	pages =	{8--12},
	month =	{June~22},
	year =	{1999},
	url =	{http://web.cps.msu.edu/\~{}hwangwey/CBAIVL/cvaivl99.ps},
	abstract =	{Fisher's discriminant analysis is very powerful for
	classification but it does not perform well when the number of classes
	is large but the number of samples in each class is small. We propose
	to resolve this problem by dynamically grouping classes at different
	levels in a tree. We recast the problem of classification as a
	regression problem so that the classification (class labels as output)
	and regression (numerical values as output) are unified. The proposed
	HDR tree automatically forms clusters in the input space guided by the
	desired output, which produces discriminant spaces. These discriminant
	spaces are organized in a coarse-to-fine structure by a tree. A unified
	size-dependent negative-log-likelihood is proposed to automatically
	handle both under-sample situations (where the number of samples of
	each cluster is smaller than the dimensionality of the discriminant
	space) and the over-sample situations where the HDR tree can reach
	near-optimal performance. For fast computation, the HDR tree has a
	logarithmic retrieval time complexity. The proposed HDR tree has been
	tested with synthetic data, face image databases, and publicly
	available data sets that use manually selected features.},
}