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6.881表示和建模的图像分析6.881 Representation and Modeling for Image Analysis |
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| 课程网址: | http://ocw.mit.edu/courses/electrical-engineering-and-computer-sc... |
| 主讲教师: | Prof. Polina Golland |
| 开课单位: | 麻省理工学院 |
| 开课时间: | 2005-01-01 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Most algorithms in computer vision and image analysis can be understood in terms of two important components: a representation and a modeling/estimation algorithm. The representation defines what information is important about the objects and is used to describe them. The modeling techniques extract the information from images to instantiate the representation for the particular objects present in the scene. In this seminar, we will discuss popular representations (such as contours, level sets, deformation fields) and useful methods that allow us to extract and manipulate image information, including manifold fitting, markov random fields, expectation maximization, clustering and others. For each concept -- a new representation or an estimation algorithm -- a lecture on the mathematical foundations of the concept will be followed by a discussion of two or three relevant research papers in computer vision, medical and biological imaging, that use the concept in different ways. We will aim to understand the fundamental techniques and to recognize situations in which these techniques promise to improve the quality of the analysis. |
| 关 键 词: | 计算机视觉; 图像分析; 建模技术; 图像信息; 流形拟合; 马尔可夫随机插值 |
| 课程来源: | 麻省理工学院公开课 |
| 最后编审: | 2024-06-02：chenjy |
| 阅读次数: | 29 |