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

2001

@article{MNP2001,
	vgclass =	{refpap},
	author =	{B. Moghaddam and C. Nastar and A. Pentland},
	title =	{A {B}ayesian similarity measure for deformable image
	matching},
	journal =	{Image and Vision Computing},
	volume =	{19},
	number =	{5},
	pages =	{235--244},
	month =	{April},
	year =	{2001},
	url =	{http://dx.doi.org/10.1016/S0262-8856(00)00059-7},
	abstract =	{We propose a probabilistic similarity measure for direct
	image matching based on a Bayesian analysis of image deformations. We
	model two classes of variation in object appearance: intra-object and
	extra-object. The probability density functions for each class are then
	estimated from training data and used to compute a similarity measure
	based on the a posteriori probabilities. Furthermore, we use a novel
	representation for characterizing image differences using a deformable
	technique for obtaining pixel-wise correspondences. This
	representation, which is based on a deformable 3D mesh in XYI-space, is
	then experimentally compared with two simpler representations:
	intensity differences and optical flow. The performance advantage of
	our deformable matching technique is demonstrated using a typically
	hard test set drawn from the US Army's FERET face database.},
}