Solving Minimum Cost Lifted Multicut Problems by Node Agglomeration
Solving Minimum Cost Lifted Multicut Problems by Node Agglomeration
复制标题
通过节点聚集解决最小成本提升的多割问题
DOI:
10.1007/978-3-030-20870-7_5
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发表时间:
2019
期刊:
影响因子:
--
通讯作者:
Margret Keuper
中科院分区:
文献类型:
--
作者:
Amirhossein Kardoost;Margret Keuper
Despite its complexity, the minimum cost lifted multicut problem has found a wide range of applications in recent years, such as image and mesh decomposition or multiple object tracking. Its solutions are decompositions of a graph into an optimal number of segments which are optimized w.r.t. a cost function defined on a superset of the edge set. While the currently available solvers for this problem provide high quality solutions in terms of the task to be solved, they can have long computation times for more difficult problem instances. Here, we propose two variants of a heuristic solver (primal feasible heuristic), which greedily generate solutions within a bounded amount of time. Evaluations on image and mesh segmentation benchmarks show the high quality of these solutions.
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期刊:
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2011 International Conference on Computer Vision
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DOI:
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发表时间:
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期刊:
2017 IEEE International Conference on Computer Vision (ICCV)
影响因子:
--
作者:
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通讯作者:
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