Finding Deformable Shapes Using Loopy Belief Propagation
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Abstract
A novel deformable template is presented which detects and localizes shapes in grayscale images. The template is formulated as a Bayesian graphical model of a two-dimensional shape contour, and it is matched to the image using a variant of the belief propagation (BP) algo- rithm used for inference on graphical models. The algorithm can localize a target shape contour in a cluttered image and can accommodate arbi- trary global translation and rotation of the target as well as signi?cant shape deformations, without requiring the template to be initialized in any special way (e.g. near the target).
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