Graph cuts with shape priors for segmentation

This paper investigates segmentation of images and videos using graph cuts and shape priors. Graph cuts is used to find the global optimum of a cost function based on the region and boundary properties of the image or video. The region and boundary properties are estimated using certain pixels marked by the user. A shape prior term is added to this cost function to bias the solution towards a known shape. In this work, a circular shape prior defined by center and radius parameters is used. Powell’s minimization algorithm is used to align the shape prior with the object to be segmented. The average location of the user-marked pixels is used as a starting point to initialize Powell’s method. Accurate image and video segmentations are achieved with minimal user input. The results obtained when including shape priors are compared to those using just the region and boundary properties in the graph cut. Although only a circular prior is used in this work, the concepts can be extended to any parametric shape prior that determines the shape of the desired object. In this paper, graph cuts and shape priors are used to segment faces from images and videos.