---
res:
bibo_abstract:
- Motivated by various applications to computer vision, we consider the convex cost
tension problem, which is the dual of the convex cost flow problem. In this paper,
we first propose a primal algorithm for computing an optimal solution of the problem.
Our primal algorithm iteratively updates primal variables by solving associated
minimum cut problems. We show that the time complexity of the primal algorithm
is O (K {dot operator} T (n, m)), where K is the range of primal variables and
T (n, m) is the time needed to compute a minimum cut in a graph with n nodes and
m edges. We then develop an improved version of the primal algorithm, called the
primal-dual algorithm, by making good use of dual variables in addition to primal
variables. Although its time complexity is the same as that of the primal algorithm,
we can expect a better performance in practice. We finally consider an application
to a computer vision problem called the panoramic image stitching.@eng
bibo_authorlist:
- foaf_Person:
foaf_givenName: Vladimir
foaf_name: Vladimir Kolmogorov
foaf_surname: Kolmogorov
foaf_workInfoHomepage: http://www.librecat.org/personId=3D50B0BA-F248-11E8-B48F-1D18A9856A87
- foaf_Person:
foaf_givenName: Akiyoshi
foaf_name: Shioura, Akiyoshi
foaf_surname: Shioura
bibo_doi: 10.1016/j.disopt.2009.04.006
bibo_issue: '4'
bibo_volume: 6
dct_date: 2009^xs_gYear
dct_publisher: Elsevier@
dct_title: New algorithms for convex cost tension problem with application to computer
vision@
...