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M16028 - Application of M LH for improvement of depth maps produced by D ERS. Olgierd Stankiewicz Krzysztof Wegner team supervisor: Marek Domański Chair of Multimedia Telecommunications and Microelectronics Poznań University of Technology, Poland. February 1st, 2009, Lausanne. Introduction. - PowerPoint PPT Presentation
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M16028 - Application of MLH for improvement of depth maps
produced by DERS
February 1st, 2009, Lausanne
Olgierd StankiewiczKrzysztof Wegner
team supervisor: Marek DomańskiChair of Multimedia Telecommunications and Microelectronics
Poznań University of Technology, Poland
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Introduction
Results of experiments in M16027 Already existing tool, presented to
MPEG in M15338 Used for improvement of DERS
(Nagoya) instead of PUT
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What is MLH?
Mid-Level Hypothesis algorithm Post-processing tool that
introduces sub-pixel precision to already estimated depth maps,
Low computational complexity
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Experiments
Similar to EEs, according to guidlines in W9991,
MLH upgraded to be DERS compatible Configuration files Depth maps
Limited set of sequences
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Alt MoabitPSNR of synthesis for view 8 based on views 7 and 10
(Camera Distance 1)
33,8
34
34,2
34,4
34,6
34,8
35
35,2
35,4
35,6
35,8
36
0 0,5 1 1,5 2 2,5 3 3,5 4 4,5
Smoothing coefficient
MLH
Ref-Pel
Ref-HPel
PSNR of synthesis for view 8 based on views 7 and 10(Camera Distance 2)
33,5
34
34,5
35
35,5
36
0 0,5 1 1,5 2 2,5 3 3,5 4 4,5
Smoothing coefficient
MLH
Ref-Pel
Ref-HPel
PSNR of synthesis for view 8 based on views 7 and 10(Camera Distance 3)
34
34,2
34,4
34,6
34,8
35
35,2
35,4
35,6
0 0,5 1 1,5 2 2,5 3 3,5 4 4,5
Smoothing coefficient
MLH
Ref-Pel
Ref-HPel
PSNR of synthesis for view 8 based on views 7 and 10(Camera Distance 4)
34
34,2
34,4
34,6
34,8
35
35,2
35,4
35,6
0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 5 5,5
Smoothing coefficient
MLH
Ref-Pel
Ref-HPel
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Lovebird 1PSNR of synthesis for view 8 based on views 7 and 10
(Camera Distance 1)
26
26,5
27
27,5
28
28,5
29
0 0,5 1 1,5 2 2,5 3 3,5 4 4,5
Smoothing coefficient
MLH
Ref-Pel
Ref-HPel
PSNR of synthesis for view 8 based on views 7 and 10(Camera Distance 2)
27,6
27,7
27,8
27,9
28
28,1
28,2
28,3
28,4
28,5
28,6
0 0,5 1 1,5 2 2,5 3 3,5 4 4,5
Smoothing coefficient
MLH
Ref-Pel
Ref-HPel
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Book arrivalPSNR of synthesis for view 8 based on views 7 and 10
(Camera Distance 1)
34
34,5
35
35,5
36
36,5
37
37,5
0 0,5 1 1,5 2 2,5 3 3,5 4 4,5
Smoothing coefficient
MLH
Ref-Pel
Ref-HPel
PSNR of synthesis for view 8 based on views 7 and 10(Camera Distance 2)
35
35,5
36
36,5
37
37,5
0 0,5 1 1,5 2 2,5 3 3,5 4 4,5
Smoothing coefficient
MLH
Ref-Pel
Ref-HPel
PSNR of synthesis for view 8 based on views 7 and 10(Camera Distance 3)
31,5
32
32,5
33
33,5
34
34,5
35
35,5
36
36,5
0 0,5 1 1,5 2 2,5 3 3,5 4 4,5
Smoothing coefficient
MLH
Ref-Pel
Ref-HPel
PSNR of synthesis for view 8 based on views 7 and 10(Camera Distance 4)
34,9
35
35,1
35,2
35,3
35,4
35,5
35,6
35,7
35,8
35,9
0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 5 5,5
Smoothing coefficient
MLH
Ref-Pel
Ref-HPel
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NewspaperPSNR of synthesis for view 8 based on views 7 and 10
(Camera Distance 1)
23
24
25
26
27
28
29
0 0,5 1 1,5 2 2,5 3 3,5 4 4,5
Smoothing coefficient
MLH
Ref-Pel
Ref-HPel
PSNR of synthesis for view 8 based on views 7 and 10(Camera Distance 2)
27
27,5
28
28,5
29
29,5
30
30,5
0 0,5 1 1,5 2 2,5 3 3,5 4 4,5
Smoothing coefficient
MLH
Ref-Pel
Ref-HPel
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DERS – QPel precision
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DERS – Pixel precision
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DERS + MLH –> QPel precision
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Conclusions - improvement
Compared to DERS Pel precision 0.5 dB to 2 dB of PSNR gain
Compared to DERS HPel precision up to 1 dB of PSNR gain
Subjectively more ‘smooth’
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Conclusions
Can be used with little effort Low computational cost Further test over variety of
sequences are encouraged
