In the domain of shape modeling researchers have investigated various shape models in the abstract. In particular, Zhu and co-workers have proposed a maximum-entropy based model of object shape derived from data. In this paper we investigate the possibility of using such a shape model for image segmentation. To our knowledge, this is the first attempt at using such models to solve practical pro...

We present a modification of the Mumford–Shah functional and its cartoon limit which allows the incorporation of statistical shape knowledge in a single energy functional. We show segmentation results on artificial and real–world images with and without prior shape information. In the case of occlusion and strongly cluttered background the shape prior significantly improves segmentation. Finall...

The “light-from-above” prior is invoked to simplify and expedite complex visual processing. This prior is observed in visual search and shape judgments with shaded stimuli, where perceived shape and ease of target identification are both affected by stimulus orientation. In addition, perceived surface reflectance varies with surface orientation in a manner consistent with assumed overhead light...

The "light-from-above" prior is invoked to simplify and expedite complex visual processing. This prior is observed in visual search and shape judgments with shaded stimuli, where perceived shape and ease of target identification are both affected by stimulus orientation. In addition, perceived surface reflectance varies with surface orientation in a manner consistent with assumed overhead light...

We present a shape optimization approach to compute patient-specific models in customized prototyping applications. We design a coupled shape prior to model the transformation between a related pair of surfaces, using a nonparametric joint probability density estimation. The coupled shape prior forces with the help of application-specific data forces and smoothness forces drive a surface deform...