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

1999

@inproceedings{MuR1999,
	vgclass =	{refpap},
	vgproject =	{cbir},
	author =	{Stefan M\"{u}ller and Gerhard Rigoll},
	title =	{Improved Stochastic Modeling of Shapes for Content-Based
	Image Retrieval},
	booktitle =	{IEEE Workshop on Content-based Access of Image and Video
	Libraries (CBAIVL'99)},
	address =	{Fort Collins, Colorado, USA},
	pages =	{23--27},
	month =	{June~22},
	year =	{1999},
	url =	{http://www.fb9-ti.uni-duisburg.de/publ.ps/99/cbaivl99.ps.gz},
	abstract =	{Recent advances in the stochastic modeling of shapes for
	content-based image database retrieval are presented in this paper.
	These advances include an integrated approach to shape and color-based
	retrieval, where the cues color and shape are both utilized in a local
	rather than a global way, as well as a novel deformation tolerant
	method based on (pseudo-) two-dimensional stochastic models. The
	stochastic modeling itself is based on the use of HMMs, whereas the
	feature extraction is a polar sampling technique which is also known
	as shape matrix. In an earlier publication, it has been demonstrated
	that this combination of feature extraction and HMMs is able to perform
	an elastic matching, which is especially needed in sketch based image
	retrieval. The use of streams (sets of features that are assumed to be
	statistically independent) within the HMM framework allows the
	integration of shape and color derived features into a single model,
	thereby allowing to control the influence of the different streams via
	stream weights. Furthermore, these stream weights can also be utilized
	in order to integrate weighting factors, which have been derived in
	the context of shape matrices, in order to achieve a more objective
	comparison between shapes. The weighting factors are based on the fact
	that the sampling density is not constant with the polar sampling
	raster.},
}