In the present paper we address the problem of establishing contours in static monocular scenes. We propose to use features from unified edge and key-point detection to drive an active contour model. We present a framework for image segmentation consisting of, (a) detection of 1D and 2D intensity discontinuities, i.e. general edges and key-points, (b) reformulation of the active contour model to an expanding version, called ``growing snake'', (c) automatic generation of suitable start-points, (d) image and internal geometry driven optimized expansion, and (e) controlled termination. The objective is to explore the potential of a fully automatic segmentation scheme. The performance and present limitations of growing snakes are demonstrated on images representative for diverse classes of scenes.