Abstract. We propose a probabilistic segmentation scheme, which is widely applicable to some extend. Besides the segmentation itself our model incorporates object specific shading. Dependent upon application, the latter is interpreted either as a perturbation or as meaningful object characteristic. We discuss the recognition task for segmentation, learning tasks for parameter estimation as well as different formulations of shading estimation tasks
