图 书 馆
离散模型中的映射推理MAP inference in Discrete Models |
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| 课程网址: | http://videolectures.net/bmvc2012_kohli_discrete_models/ |
| 主讲教师: | Pushmeet Kohli |
| 开课单位: | 微软公司 |
| 开课时间: | 2012-10-09 |
| 课程语种: | 英语 |
| 中文简介: |  计算机视觉中的许多问题都是以离散变量的随机形式表述的。示例包括从图像分割，光流和立体重建等低级视觉到对象识别等高阶视觉。通常，目标是推断随机变量的最可能值，称为最大后验（MAP）估计。在计算机科学的多个领域（例如计算机视觉，机器学习，理论）已经对此进行了广泛的研究，并且所产生的算法极大地帮助获得了针对许多问题的准确而可靠的解决方案。这些算法非常高效，可以在多项式时间内为一类重要的模型找到全局（或局部强）最优解。因此，它们导致计算机视觉和信息工程领域中随机场模型的使用显着增加。本教程针对希望使用和理解这些算法来解决计算机视觉和信息工程新问题的研究人员。不会假设有概率模型或离散优化的先验知识。本教程将回答以下问题：（a）如何使用随机场的MAP推理来形式化和解决一些已知的视觉问题？ （b）MAP推理算法有哪些不同类型？ （c）它们如何工作？ （d）该领域最近的发展和尚待解决的问题是什么？ |
| 课程简介: | Many problems in Computer Vision are formulated in form of a random filed of discrete variables. Examples range from low-level vision such as image segmentation, optical flow and stereo reconstruction, to high-level vision such as object recognition. The goal is typically to infer the most probable values of the random variables, known as Maximum a Posteriori (MAP) estimation. This has been widely studied in several areas of Computer Science (e.g. Computer Vision, Machine Learning, Theory), and the resulting algorithms have greatly helped in obtaining accurate and reliable solutions to many problems. These algorithms are extremely efficient and can find the globally (or strong locally) optimal solutions for an important class of models in polynomial time. Hence, they have led to a significant increase in the use of random field models in computer vision and information engineering in general. This tutorial is aimed at researchers who wish to use and understand these algorithms for solving new problems in computer vision and information engineering. No prior knowledge of probabilistic models or discrete optimization will be assumed. The tutorial will answer the following questions: (a) How to formalize and solve some known vision problems using MAP inference of a random field? (b) What are the different genres of MAP inference algorithms? (c) How do they work? (d) What are the recent developments and open questions in this field? |
| 关 键 词: | 离散模型; 计算机算法 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2020-11-08：zyk |
| 最后编审: | 2020-11-09：chenxin |
| 阅读次数: | 61 |