图 书 馆
立体视觉的无监督学习Unsupervised Learning for Stereo Vision |
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| 课程网址: | http://videolectures.net/mlss09us_mcallester_ulsv/ |
| 主讲教师: | David McAllester |
| 开课单位: | 芝加哥丰田技术学院 |
| 开课时间: | 2009-07-30 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We consider the problem of learning to estimate depth from stereo image pairs. This can be formulated as unsupervised learning - the training pairs are not labeled with depth. We have formulated an algorithm which maximizes conditional likelihood the left image given right image in a model that involves latent information (depth). This unsupervised learning algorithm implicitly trains shape from texture and shape from shading monocular depth cues. The talk will present pragmatic results in the stereo vision problem as well as a general formulation of models and methods for maximizing conditional likelihood in a latent variable model where we wish to interpret the latent information as "labels". |
| 关 键 词: | 立体图像; 无监督学习; 条件似然性; 在潜变量模型 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-07-18：cjy |
| 阅读次数: | 75 |