Title
A continuous max-flow approach to potts model
Abstract
We address the continuous problem of assigning multiple (unordered) labels with the minimum perimeter. The corresponding discrete Potts model is typically addressed with a-expansion which can generate metrication artifacts. Existing convex continuous formulations of the Potts model use TV-based functionals directly encoding perimeter costs. Such formulations are analogous to 'min-cut' problems on graphs. We propose a novel convex formulation with a continous 'max-flow' functional. This approach is dual to the standard TV-based formulations of the Potts model. Our continous max-flow approach has significant numerical advantages; it avoids extra computational load in enforcing the simplex constraints and naturally allows parallel computations over different labels. Numerical experiments show competitive performance in terms of quality and significantly reduced number of iterations compared to the previous state of the art convex methods for the continuous Potts model.
Year
DOI
Venue
2010
10.1007/978-3-642-15567-3_28
ECCV (6)
Keywords
Field
DocType
potts model,convex continuous formulation,novel convex formulation,art convex method,continuous potts model,continuous max-flow approach,continous max-flow approach,potts model use,tv-based functionals,continuous problem,corresponding discrete potts model,parallel computer
Applied mathematics,Graph,Mathematical optimization,Computer science,Regular polygon,Simplex,Artificial intelligence,Maximum flow problem,Machine learning,Potts model,Computation,Encoding (memory)
Conference
Volume
ISSN
ISBN
6316
0302-9743
3-642-15566-9
Citations 
PageRank 
References 
73
2.09
21
Authors
4
Name
Order
Citations
PageRank
Jing Yuan118212.30
Egil Bae239115.56
Xue-Cheng Tai32090131.53
Yuri Boykov47601497.20