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PMBP：对应场估计的PatchMatch信念传播PMBP: PatchMatch Belief Propagation for Correspondence Field Estimation |
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| 课程网址: | http://videolectures.net/bmvc2012_besse_belief_propagation/ |
| 主讲教师: | Frederic Besse |
| 开课单位: | 伦敦大学学院 |
| 开课时间: | 2012-10-09 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | PatchMatch is a simple, yet very powerful and successful method for optimizing continuous labelling problems. The algorithm has two main ingredients: the update of the solution space by sampling and the use of the spatial neighbourhood to propagate samples. We show how these ingredients are related to steps in a specific form of belief propagation in the continuous space, called Particle Belief Propagation (PBP). However, PBP has thus far been too slow to allow complex state spaces. We show that unifying the two approaches yields a new algorithm, PMBP, which is more accurate than PatchMatch and orders of magnitude faster than PBP. To illustrate the benefits of our PMBP method we have built a new stereo matching algorithm with unary terms which are borrowed from the recent PatchMatch Stereo work and novel realistic pairwise terms that provide smoothness. We have experimentally verified that our method is an improvement over state-of-the-art techniques at sub-pixel accuracy level. |
| 关 键 词: | 优化连续标记问题; 更新解空间; 空间邻域 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2021-02-04：nkq |
| 阅读次数: | 93 |