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

1996

@article{HMS1996,
	vgclass =	{refpap},
	author =	{Parag Havaldar and G\'{e}rard Medioni and Fridtjof Stein},
	title =	{Perceptual Grouping for Generic Recognition},
	journal =	{International Journal of Computer Vision},
	volume =	{20},
	number =	{1/2},
	pages =	{59--80},
	month =	{October},
	year =	{1996},
	abstract =	{We address the problem of recognition of generic objects
	from a single intensity image. This precludes the use of purely
	geometrical methods which assume that models are geometrically and
	precisely designed. Instead, we propose to use descriptions in terms of
	features and their qualitative  geometric relationships. To succeed, it
	is clear that these features need to be high level, rather than points
	or lines. We propose to detect groups using perceptual organization
	criteria such as proximity, symmetry, parallelism, and closure. The
	detection of these features is performed in an efficient way using
	proximity indexing. Since many groups are created, we also perform
	selection of relevant groups by organizing them into sets of similar
	perceptual content. Finally we present an implementation of a
	recognition system using these sets as primitives. It is an efficient
	colored graph matching algorithm using the adjacency matrix
	representation of a graph. Using indexing, we retrieve matching
	hypotheses, which are verified against each other with respect to
	topological constraints. Groups of consistent hypotheses represent
	detected model instances in a scene. The complete system is illustrated
	on real images. We also discuss further extensions.},
}