Departmental Papers (CIS)

Contour cut: Identifying salient contour in images by solving a Hermitian eigenvealue problem

Jianbo Shi, University of Pennsylvania
Ryan Kennedy, University of Pennsylvania
Jean H. Gallier, University of Pennsylvania

Document Type Conference Paper

Kennedy, R., Gallier, J., & Shi, J. IEEE Conference on Computer Vision and Pattern Recognition. 2011

©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Abstract

The problem of finding one-dimensional structures in images and videos can be formulated as a problem of searching for cycles in graphs. In [11], an untangling-cycle cost function was proposed for identifying persistent cycles in a weighted graph, corresponding to salient contours in an image. We have analyzed their method and give two significant improvements. First, we generalize their cost function to a contour cut criterion and give a computational solution by solving a family of Hermitian eigenvalue problems. Second, we use the idea of a graph circulation, which ensures that each node has a balanced in- and out-flow and permits a natural random-walk interpretation of our cost function. We show that our method finds far more accurate contours in images than [11]. Furthermore, we show that our method is robust to graph compression which allows us to accelerate the computation without loss of accuracy.

 

Date Posted: 16 July 2012