Transcript Slide 1

M16757 – An enhancement of Depth
Estimation Reference Software with
use of soft-segmentation
Olgierd Stankiewicz
Krzysztof Wegner
team supervisor: Marek Domański
Chair of Multimedia Telecommunications and Microelectronics
Poznań University of Technology, Poland
July, 2009, London
Introduction
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Matching of images
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DERS
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Block matching tool
Segmentation tool
Proposal
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Soft-segmentation tool
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Depth Estimation
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Block matching in DERS
Center
point
in window
Matching
window
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Soft-segmentation matching
(weighted window)
Right
image
Center
point
in window
Final
Comparison
mask
Left
image
Soft-segmentation mask
Blocks of
(color similarity only)
matched images
Soft-segmentation mask
(color similarity
and pixel proximity)
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Soft-segmentation mask
W P, P'  e
W(P,P’)
center point P
I(P)
|P-P’|
c
d

I ( P )  I ( P ')
c

P P'
d
–soft-segmentation mask around
– intensity of image at point P
– Euclidian distance between P and P’
– color similarity parameter of the tool
– distance similarity parameter of the tool
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Similarity measure
Similarity ( PL , PR ) 
W
L
PL ', PR 'window
( PL , PL ' )  W R ( PR , PR ' )  I R ( PR )  I L ( PL )
W
L
PL ', PR 'window
( PL , PL ' )  WR ( PR , PR ' )
where:
PL, PR
PL’, PR’
WL(PL,PL’)
WR(PR,PR’)
IL(PL)
IR(PR)
– center point in processed frame (left/right image)
– processed point in processed frame (left/right image)
– soft-segmentation mask around center point P (left image)
– soft-segmentation mask around center point P (right image)
– intensity of image at point P (left image)
– intensity of image at point P (right image)
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Quality evaluation
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DERS vs soft-segmentation tool
(SOFT) – Pel precision
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DERS vs soft-segmentation tool
(SOFT) – HPel precision
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DERS vs soft-segmentation tool
(SOFT) – QPel precision
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Conclusions 1/3
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The quality of synthesis
is better that the reference up to
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1,5dB (Pel)
1,7dB (HPel)
0,5dB (QPel)
The gain of quality decreases with higher
pixel precisions – probably due to lack of
interpolation of center view in higher
precision modes.
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Conclusions 2/3
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The proposed tool is integrated in
current DERS version 3.0 and can be
easily added to the future versions.
Use of soft-segmentation (instead of
hard segmentation) prevents arbitrary
decisions in estimation process – lesser
flickering.
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Conclusions 3/3
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The gains are higher in case of bigger
camera distance – probably due to
better usage of structural information.
Computation time is slightly longer that
„block matching mode” in the DERS,
but substantially shorter that with use
of segmentation tool of DERS.
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Recommendations
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Integration of new tool in the future
version of DERS.
Fully fledged tests of the proposed tool
on next pass of Exploration
Experiments.
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