DocumentCode
3549194
Title
Energy minimization via graph cuts: settling what is possible
Author
Freedman, Daniel ; Drineas, Petros
Author_Institution
Dept. of Comput. Sci., Rensselaer Polytech. Inst., Troy, NY, USA
Volume
2
fYear
2005
fDate
20-25 June 2005
Firstpage
939
Abstract
The recent explosion of interest in graph cut methods in computer vision naturally spawns the question: what energy functions can be minimized via graph cuts? This question was first attacked by two papers of Kolmogorov and Zabih, in which they dealt with functions with pair-wise and triplewise pixel interactions. In this work, we extend their results in two directions. First, we examine the case of k-wise pixel interactions; the results are derived from a purely algebraic approach. Second, we discuss the applicability of provably approximate algorithms. Both of these developments should help researchers best understand what can and cannot be achieved when designing graph cut based algorithms.
Keywords
computer vision; functions; graph theory; minimisation; approximate algorithm; computer vision; energy function minimization; graph cut method; k-wise pixel interaction; Algorithm design and analysis; Application software; Computer science; Computer vision; Explosions; Minimization methods; NP-complete problem; Polynomials; Stereo vision; Sufficient conditions; energy minimization; graph cuts;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on
ISSN
1063-6919
Print_ISBN
0-7695-2372-2
Type
conf
DOI
10.1109/CVPR.2005.143
Filename
1467543
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