An efficient graph cut algorithm for computer vision problems

Authors:
Chetan Arora;Subhashis Banerjee;Prem Kalra;S. N. Maheshwari
Affiliations:
Department of Computer Science and Engineering, Indian Institute of Technology, Delhi, India;Department of Computer Science and Engineering, Indian Institute of Technology, Delhi, India;Department of Computer Science and Engineering, Indian Institute of Technology, Delhi, India;Department of Computer Science and Engineering, Indian Institute of Technology, Delhi, India
Venue:
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Year:
2010

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Abstract

Graph cuts has emerged as a preferred method to solve a class of energy minimization problems in computer vision. It has been shown that graph cut algorithms designed keeping the structure of vision based flow graphs in mind are more efficient than known strongly polynomial time max-flow algorithms based on preflow push or shortest augmenting path paradigms [1]. We present here a new algorithm for graph cuts which not only exploits the structural properties inherent in image based grid graphs but also combines the basic paradigms of max-flow theory in a novel way. The algorithm has a strongly polynomial time bound. It has been bench-marked using samples from Middlebury [2] and UWO [3] database. It runs faster on all 2D samples and is at least two to three times faster on 70% of 2D and 3D samples in comparison to the algorithm reported in [1].