发帖
雷达卡
摘要翻译：
我们提出了alpha展开beta-收缩移动，它是广泛使用的alpha-beta交换和alpha展开近似能量最小化算法的一个简单推广。我们证明，在某种意义上，这些移动控制着alpha-beta-swap和alpha-expansion移动，但与以前的推广不同，新的移动不需要额外的假设，并且在多项式时间内仍然是可解的。我们用新的移动展示了有希望的实验结果，我们相信它可以用于目前使用alpha展开的任何上下文。
---
英文标题：
《Generalized Fast Approximate Energy Minimization via Graph Cuts:
Alpha-Expansion Beta-Shrink Moves》
---
作者：
Mark Schmidt (INRIA Paris - Rocquencourt), Karteek Alahari (INRIA
Paris - Rocquencourt)
---
最新提交年份：
2011
---
分类信息：
一级分类：Computer Science 计算机科学
二级分类：Computer Vision and Pattern Recognition 计算机视觉与模式识别
分类描述：Covers image processing, computer vision, pattern recognition, and scene understanding. Roughly includes material in ACM Subject Classes I.2.10, I.4, and I.5.
涵盖图像处理、计算机视觉、模式识别和场景理解。大致包括ACM课程I.2.10、I.4和I.5中的材料。
--
一级分类：Computer Science 计算机科学
二级分类：Artificial Intelligence 人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
--
---
英文摘要：
We present alpha-expansion beta-shrink moves, a simple generalization of the widely-used alpha-beta swap and alpha-expansion algorithms for approximate energy minimization. We show that in a certain sense, these moves dominate both alpha-beta-swap and alpha-expansion moves, but unlike previous generalizations the new moves require no additional assumptions and are still solvable in polynomial-time. We show promising experimental results with the new moves, which we believe could be used in any context where alpha-expansions are currently employed.
---
PDF链接：
https://arxiv.org/pdf/1108.5710
京公网安备 11010802022788号
