Dynamic programming and graph algorithms in computer vision.
Dynamic programming and graph algorithms in computer vision.
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DOI：
10.1109/tpami.2010.135
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发表时间：
2011-04
影响因子：
23.6
通讯作者：
Zabih R
中科院分区：
文献类型：
--
作者：
Felzenszwalb PF;Zabih R
优化是一种表达和解决广泛领域问题的强大范式，并已成功地应用于许多视觉问题。离散优化技术特别有趣，因为通过仔细地利用问题结构，它们通常提供有关解决方案质量的重要保证。在本文中，我们简要回顾了动态规划和图算法，并讨论了如何将这些离散优化技术应用于一些经典视觉问题的代表性示例。我们专注于立体的低层次视觉问题；交互式目标分割的中级问题；以及基于模型的高级识别问题。
Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting, since by carefully exploiting problem structure they often provide non-trivial guarantees concerning solution quality. In this paper we briefly review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo; the mid-level problem of interactive object segmentation; and the high-level problem of model-based recognition.