Geodesic Active Contours with Combined Shape and Appearance Priors

Abstract

We present a new object segmentation method that is based on geodesic active contours with combined shape and appearance priors. It is known that using shape priors can significantly improve object segmentation in cluttered scenes and occlusions. Within this context, we add a new prior, based on the appearance of the object, (i.e., an image) to be segmented. This method enables the appearance pattern to be incorporated within the geodesic active contour framework with shape priors, seeking for the object whose boundaries lie on high image gradients and that best fits the shape and appearance of a reference model. The output contour results from minimizing an energy functional built of these three main terms. We show that appearance is a powerful term that distinguishes between objects with similar shapes and capable of successfully segment an object in a very cluttered environment where standard active contours (even those with shape priors) tend to fail.