BMVC 2004, Kingston, 7th-9th Sept, 2004
A Bayesian Occlusion Model for Sequential Object Matching
T. Tamminen and J. Lampinen (Helsinki University of Technology, Finland)
We consider the problem of locating instances of a known object in a
novel scene by matching the fiducial features of the object. Our approach
to the problem consists of two parts: a model for the appearance of the features
and a model for the shape of the object. We then bind these parts together
in a Bayesian framework and match the features sequentially, using
the information about the locations of previously matched features. Into this
matching system we add a Bayesian model for dealing with features that are
not detected due to occlusion or abnormal appearance. Our system yields
promising results, losing little matching accuracy even for heavily occluded
objects.
(pdf article)