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PMBP: PatchMatch Belief Propagation for Correspondence Field Estimation
Published on Oct 09, 20124707 Views
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
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PMBP: PatchMatch Belief Propagation for Correspondence Field Estimation00:00
Correspondence fields00:15
Stereo matching (1)00:18
Stereo matching (2)00:28
Optical flow (1)00:36
Optical flow (2)00:48
Let us consider stereo matching00:56
Stereo matching (3)01:04
Stereo matching (4)01:07
Stereo matching (5)01:15
Stereo matching (6)01:23
Problems (1)01:33
Discontinuities (1)01:54
Discontinuities (2)02:14
Discontinuities (3)02:22
Discontinuities (4)02:36
Discontinuities (5)02:48
Problems (2)03:02
Non-fronto-parallel planes (1)03:10
Non-fronto-parallel planes (2)03:14
Non-fronto-parallel planes (3)03:19
Non-fronto-parallel planes (4)03:23
Non-fronto-parallel planes (5)03:39
Problems (3)04:06
Let’s try something04:14
Random correspondences04:17
Randomisation (1)04:29
Randomisation (2)04:43
Random correspondences04:56
A few good matches05:04
Local minima05:18
Idea of PatchMatch05:31
Starting point05:44
Propagation: iteration 105:47
Iteration 205:57
Iteration 305:59
Final, post-processed06:06
Works great on Teddy! But…06:31
Problem (1)06:35
Problem (2)06:42
Problem (3)06:50
Problem (4)06:53
Solution (1)07:02
Solution (2)07:10
High dimensional label space07:29
Particle BP07:50
Particle BP: slow07:57
Summary so far08:31
Yes!08:41
Our first contribution08:44
Algorithmic Pizza08:54
Base09:08
PatchMatch09:14
Particle BP09:20
Second contribution: PMBP09:29
PMBP Recipe: 3 ingredients10:03
PMBP Recipe (1)10:16
PMBP Recipe (2)10:45
PMBP Recipe (3)11:00
Results11:11
2D matching (1)11:18
2D matching (2)11:46
2D matching (3)11:50
2D matching (4)11:53
PM – PBP – PMBP12:14
Denoising13:43
PatchMatch13:49
Ours14:01
Stereo - Effect of smoothness14:07
Middlebury14:41
Conclusion14:53
Thank you15:23