Occluded Bilateral EPI Regularization2nd Workshop on Light Fields for Computer VisionJuly 26, 2017
Overview
OBER - Hendrik Schilling - July 26, 2017 1/15
Overview
standard minimization approach→ data term, smoothness term, solversome twists for crisper and smoother resultssome (over) simplifications
Key Insight
OBER - Hendrik Schilling - July 26, 2017 2/15
3D Reconstruction as Minimization Problem
inverse problemunderconstrainednon-convex
Key Insight
OBER - Hendrik Schilling - July 26, 2017 3/15
Key InsightsThe Problem is inherently non-differentiable due to
occlusions→ enforcing differentiabiliy will result in sub-optimal results
SecondaryIntermediate steps impair occlusion border & fine detail
performance→ formulate error metrics in input domain
Method
OBER - Hendrik Schilling - July 26, 2017 4/15
Data Term
Method
OBER - Hendrik Schilling - July 26, 2017 5/15
Smoothness Term
0.7
0.8
0.8
0.5 0.8 0.5
0.20.30.80.80.2
0.3
0.4
0.3
0.2 0.2
0.5
1.0
0.9
0.2
0.1
1.0
0.7 0.6
0.8
0.5
0.6
0.7
candidate d = candidate d =
modified bilateral filterevaluate both color and disparityhard thresholds → crisp occlusion boundaries
Method
OBER - Hendrik Schilling - July 26, 2017 6/15
Solver
Algorithm 1 Randomized Solver1: for 20 iterations do2: for Every disp map pixel do3: Calc error for current depth4: Calc error for depth candidates5: Keep best result6: end for7: end for
Method
OBER - Hendrik Schilling - July 26, 2017 7/15
Depth Candidates
random changerandom guessrandom (large range) neighbourdirect neighbour
Method
OBER - Hendrik Schilling - July 26, 2017 8/15
Propagationeven
pixel processing order neighbour candidates
odd
itera
tion
Results
OBER - Hendrik Schilling - July 26, 2017 9/15
groundtruth
disparitycenterview
disparity
BadPix(0.07)
OBER-cross+ANP SPO-MO2nd best BadPix(0.07)
mesh of OBER result(as viewed from above)
Results
OBER - Hendrik Schilling - July 26, 2017 10/15
0.00
18.51
3.01
1.76
0.27
0.42
11.17
4.80
10.12
37.0111.78
6.02
3.52
0.53
0.940.85
16.86
22.35
9.59
20.23
12.10
55.52
17.67
9.03
5.27
0.80
1.41
1.27
25.28
33.52
14.39
30.35
18.15
74.03
23.56
12.04
7.03
1.07
1.88
1.69
33.71
44.70
19.19
40.47
24.20
OBEROBER-cross+ANPOFSY_330/DNRPS_RFRM3DESPO-MO
BadPix(0.01)
BadPix(0.03)
BadPix(0.07)
MSE
Q25
Bumpiness
Contin.
SurfacesBumpiness
Planes
Discontinuities
Fine
Fattening
Fine
Thinning
MAE
Contin.
Surfaces
MAE
Planes
Results
OBER - Hendrik Schilling - July 26, 2017 11/15
Results
OBER - Hendrik Schilling - July 26, 2017 12/15
rereference result(OFSY_330/DNR)
OBER-cross+ANP(half-size imgs)
Outlook
OBER - Hendrik Schilling - July 26, 2017 13/15
OutlookA lot of things to improve:scale space, un-occlusions, heuristics → NN, disp map → mesh
Main strength:very flexible, per-pixel adaptable solver
Outlook
OBER - Hendrik Schilling - July 26, 2017 14/15
The End
OBER - Hendrik Schilling - July 26, 2017 15/15
The End
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