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ECCV
2010
Springer

An Efficient Graph Cut Algorithm for Computer Vision Problems

10 years 9 months ago
An Efficient Graph Cut Algorithm for Computer Vision Problems
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].
Chetan Arora, Subhashis Banerjee, Prem Kalra, S. N
Added 02 Mar 2011
Updated 02 Mar 2011
Type Journal
Year 2010
Where ECCV
Authors Chetan Arora, Subhashis Banerjee, Prem Kalra, S. N. Maheshwari
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