图 书 馆
图结构的监督学习Supervised Learning of Graph Structure |
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| 课程网址: | http://videolectures.net/simbad2011_rossi_structure/ |
| 主讲教师: | Luca Rossi |
| 开课单位: | 威尼斯卡福斯卡里大学 |
| 开课时间: | 2011-10-17 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Graph-based representations have been used with considerable success in computer vision in the abstraction and recognition of object shape and scene structure. Despite this, the methodology available for learning structural representations from sets of training examples is relatively limited. In this paper we take a simple yet effective Bayesian approach to attributed graph learning. We present a naïve node-observation model, where we make the important assumption that the observation of each node and each edge is independent of the others, then we propose an EM-like approach to learn a mixture of these models and a Minimum Message Length criterion for components selection. Moreover, in order to avoid the bias that could arise with a single estimation of the node correspondences, we decide to estimate the sampling probability over all the possible matches. Finally we show the utility of the proposed approach on popular computer vision tasks such as 2D and 3D shape recognition. |
| 关 键 词: | 计算机视觉; 贝叶斯方法; 属性图学习 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-09-21：cwx |
| 阅读次数: | 68 |