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

2004

@article{QFF2004,
	vgclass =	{refpap},
	author =	{Guoping Qiu and Xia Feng and Jianzhong Fang},
	title =	{Compressing histogram representations for automatic colour
	photo categorization},
	journal =	{Pattern Recognition},
	year =	{2004},
	note =	{(in press)},
	url =	{http://dx.doi.org/10.1016/j.patcog.2004.03.006},
	abstract =	{Organizing images into semantic categories can be very
	useful for searching and browsing through large image repositories. In
	this work, we use machine learning to associate low level colour
	representations of digital colour photos with their high level semantic
	categories. We investigate the redundancy and performance of a number
	of histogram-based colour image content representations in the context
	of automatic colour photo categorization using support vector machines.
	We use principal component analysis to reduce the dimensionality of
	(high dimensional) histogram based colour descriptors and use support
	vector machines to learn to classify the images into various high level
	categories in the histograms subspaces. We present experimental results
	to demonstrate the usefulness of such an approach to organizing colour
	photos into semantic categories. Our results show that the colour
	content descriptors constructed in different ways perform quite
	differently and the performances are data dependent hence it is
	difficult to pick a "winning" descriptor. Our results demonstrate
	conclusively that all descriptors studied in this paper are highly
	redundant and that regardless of their performances, the
	dimensionalities of these histogram based colour content descriptors
	can be significantly reduced without affecting their classification
	performances.},
}