Object Segmentation Using Graph Cuts Based Active Contours

In this paper we present a graph cuts based active contours (GCBAC) approach to object segmentation problems. Our method is a combination of active contours and the optimization tool of graph cuts and differs fundamentally from traditional active contours in that it uses graph cuts to iteratively deform the contour. Consequently, it has the following advantages. (1). It has the ability to jump over local minima and provide a more global result. (2). Graph cuts guarantee continuity and lead to smooth contours free of self-crossing and uneven spacing problems. Therefore, the internal force which is commonly used in traditional energy functions to control the smoothness is no longer needed, and hence the number of parameters is greatly reduced. (3). Our approach easily extends to the segmentation of three and higher dimensional objects. In addition, the algorithm is suitable for interactive correction and is shown to always converge. Experimental results and analyses are provided.

• Type: Conference
• Year: 2003
• Where: CVPR
• Authors: Ning Xu, Ravi Bansal, Narendra Ahuja
• Keywords: Active Contours, Computer Vision, Cuts Guarantee Continuity, CVPR 2003, Graph Cuts, Smooth Contours, Traditional Active Contours