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用于鲁棒立体声预估的马尔科夫连续随机场Continuous Markov Random Fields for Robust Stereo Estimation |
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| 课程网址: | http://videolectures.net/eccv2012_yamaguchi_stereo/ |
| 主讲教师: | Laurent Itti; Koichiro Yamaguchi; Ramin Zabih |
| 开课单位: | 芝加哥丰田技术学院 |
| 开课时间: | 2012-11-12 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In this paper we present a novel slanted-plane model which reasons jointly about occlusion boundaries as well as depth. We formulate the problem as one of inference in a hybrid MRF composed of both continuous (i.e., slanted 3D planes) and discrete (i.e., occlusion boundaries) random variables. This allows us to define potentials encoding the ownership of the pixels that compose the boundary between segments, as well as potentials encoding which junctions are physically possible. Our approach outperforms the state-of-the-art on Middlebury high resolution imagery [1] as well as in the more challenging KITTI dataset [2], while being more efficient than existing slanted plane MRF methods, taking on average 2 minutes to perform inference on high resolution imagery. |
| 关 键 词: | 机器学习; 马尔科夫; 计算机应用 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2021-03-12：nkq |
| 阅读次数: | 55 |