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Presentation of our APGV 09 paper: Quality Assessment of Fractalized NPR Textures: a Perceptual Objective Metric (http://artis.inrialpes.fr/Publications/2009/BTS09/)
Citation preview
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
Quality Assessment of Fractalized NPR Textures:a Perceptual Objective Metric
Pierre Bénard Joëlle Thollot François Sillion
Grenoble Universities and CNRS / LJK
INRIA
October 2, 2009
October 2, 2009Quality Assessment of Fractilized Textures 1
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Non-Photorealistic Rendering
Inspiration in traditional illustration (drawing, painting...)
Stylization of still images and animations
• Stylization of 3D scenes
3D scenes 2D media (pigments, strokes, paper...)
Temporal coherence artifacts (popping, sliding, deformations)
October 2, 2009Quality Assessment of Fractilized Textures 2
Introduction
Introduction
[Herz98]
[GTDS04]
«Il p
leu
t b
erg
ère
», Jé
rém
y D
ep
uyd
t(2
00
5)
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Common solution: Fractalization process (e.g. [KLK+00, CTP+03, BSM+07, BBT09])
Medium = texture
Computation of multiple scales
Alpha-blending
Self-similar texture
October 2, 2009Quality Assessment of Fractilized Textures 3
Introduction
Introduction
+
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Common solution: Fractalization process (e.g. [KLK+00, CTP+03, BSM+07, BBT09])
Self-similar texture
October 2, 2009Quality Assessment of Fractilized Textures 4
Introduction
Introduction
+
[BBT09]
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Issues:
New features / new frequencies
Global contrast loss
Deformations
Fractalized textures visually dissimilar to the original
How to evaluate this dissimilarity ?
• Artists / viewers = final judges of the perceived quality
User study suitable… but costly
• Quality assessment metric
automatic comparison of existing techniques
new optimization based approaches
October 2, 2009Quality Assessment of Fractilized Textures 5
Problem statement
Introduction
≠
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Input: pairs of 2D texture
• Definition:texture distortion = visual dissimilarity between original and transformed textures
• Goal: define a quantitative metric of this distortion
• Procedure:
User study ranking of texture pairs according to their distortion
Statistical analysis scale of perceived quality
Correlation investigation objective metric
• Restrictions:
No texture mapping
Static images
October 2, 2009Quality Assessment of Fractilized Textures 6
Problem statement
-1.0 -0.5 0.0 0.5 1.0
Introduction
1.2
1.0
0.8
0.6
0.4
Z-Scores
AC
E
originaltransformed
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
Previous Work
Experimental Framework
Statistical Analysis
Correlation with Objective Metrics
October 2, 2009Quality Assessment of Fractilized Textures 7
Outline
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
Previous Work
Perceptual Evaluation in NPR
Perceptual Experiment Methodologies
Experimental Framework
Statistical Analysis
Correlation with Objective Metrics
October 2, 2009Quality Assessment of Fractilized Textures 8
Outline
Previous Work
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Various methodologies:
Questionnaire [SSLR96]
Performances measurement [GRG04]
Eye tracking [SD04]
Observational study + objective metric [INC+06, MIA+08]
October 2, 2009Quality Assessment of Fractilized Textures 9
Perceptual Evaluation in NPR
Previous Work
[SSLR96]
[GRG04]
[SD04]
[INC+06 ,MIA+08]
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Rating – ex.: image and video quality assessment [SSB06, Win05]
Simple, well-understood
Large number of trials and participants, subjects training needed
• Paired comparisons – ex.: tone mapping comparison [LCTS05, ČWNA08]
Straightforward forced choices
Quadratic complexity effect of fatigue
• Ranking – ex.: high quality global illumination [SFWG04]
Least time consuming task, invariant under stretching
Complicated task
October 2, 2009Quality Assessment of Fractilized Textures 10
Perceptual Experiment Methodologies
Previous Work
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
Previous Work
Experimental Framework
Stimuli
Procedure
Statistical Analysis
Correlation with Objective Metrics
October 2, 2009Quality Assessment of Fractilized Textures 11
Outline
Experimental Framework
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• 2 sets of 10 textures pairs of NPR media
October 2, 2009Quality Assessment of Fractilized Textures 12
Stimuli
(Near-)regular
patterns
Irregular
patternsGrid Dots Hatching
Cross-
hatchingPaper NoisePaint Pigments
S1
S2
Experimental Framework
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• 2 sets of 10 textures pairs of NPR media
• Fractalized with 3 scales
October 2, 2009Quality Assessment of Fractilized Textures 13
Stimuli
(Near-)regular
patterns
Irregular
patternsGrid Dots Hatching
Cross-
hatchingPaper NoisePaint Pigments
S1
S2
Orig
inal
Tra
nsfo
rme
dO
rig
inal
Tra
nsf
orm
ed
Experimental Framework
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Dynamic web interface
Number of participants (103)
Diversity of their skills in computer graphics
Control on the experimental conditions
Assessment of the statistical validity of the resulting data
October 2, 2009Quality Assessment of Fractilized Textures 14
Procedure
Naive 58.0%
Amateur/professionalinfographists
8.5%
Researcher 22.4%
Unknown 11.1%
Experimental Framework
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA) October 2, 2009Quality Assessment of Fractilized Textures 15
Procedure
Experimental Framework
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
Previous Work
Experimental Framework
Statistical Analysis
Ranking Duration
Concordance among Raters
Interval Scale of Relative Perceived Distortion
Ranking Criteria
Correlation with Objective Metrics
October 2, 2009Quality Assessment of Fractilized Textures 16
Outline
Statistical Analysis
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• 103 subjects
45 starting with S1 then S2
58 starting with S2 then S1
• Similar distribution of duration
• Comparable mean duration
No learning or fatigue effect
October 2, 2009Quality Assessment of Fractilized Textures 17
Ranking Duration
Statistical Analysis
+
+
1
1
2
2
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Merged data analysis relevant
Kendall’s coefficient of concordance (Kendall’s W) [Ken75]
• Ranking not effectively random
Significance of these coefficients validated by test
• Strong variations among textures pair
October 2, 2009Quality Assessment of Fractilized Textures 18
Concordance among Raters
Statistical Analysis
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Ordinal scale no quantification of perceived differences between pairs
October 2, 2009Quality Assessment of Fractilized Textures 19
Interval Scale of Relative Perceived Distortion
S1
S2
Statistical Analysis
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Ordinal scale no quantification of perceived differences between pairs
Thurstone’s law of comparative judgment [Tor58]
October 2, 2009Quality Assessment of Fractilized Textures 20
Interval Scale of Relative Perceived Distortion
Statistical Analysis
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0
Grid DotsHatching Paper NoisePaintPigmentsRegular
patterns
Irregular
patterns
Cross-
hatching
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0 1.5
GridDots Hatching Paper NoisePaint PigmentsNear-regular
patterns
Irregular
patterns
Cross-
hatching
S1
S2
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Unstructured textures more robust
• Textures with distinctive features more severely distorted
October 2, 2009Quality Assessment of Fractilized Textures 21
Interval Scale of Relative Perceived Distortion
Statistical Analysis
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0 1.5
GridDots Hatching Paper NoisePaint PigmentsNear-regular
patterns
Irregular
patterns
Cross-
hatching
S1
S2
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0
Grid DotsHatching Paper NoisePaintPigmentsRegular
patterns
Irregular
patterns
Cross-
hatching
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Perceived similar distortion intensity significance
Wilcoxon rank sum test
October 2, 2009Quality Assessment of Fractilized Textures 22
Interval Scale of Relative Perceived Distortion
Statistical Analysis
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0 1.5
GridDots Hatching Paper NoisePaint PigmentsNear-regular
patterns
Irregular
patterns
Cross-
hatching
S1
S2
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0
Grid DotsHatching Paper NoisePaintPigmentsRegular
patterns
Irregular
patterns
Cross-
hatching
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
Overall contrast of patterns
Feature shapes
October 2, 2009Quality Assessment of Fractilized Textures 23
Interval Scale of Relative Perceived Distortion
Statistical Analysis
S1
S2
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0
Grid DotsHatching Paper NoisePaintPigmentsRegular
patterns
Irregular
patterns
Cross-
hatching
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0 1.5
GridDots Hatching Paper NoisePaint PigmentsNear-regular
patterns
Irregular
patterns
Cross-
hatching
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
Overall contrast of patterns
Feature shapes
October 2, 2009Quality Assessment of Fractilized Textures 24
Interval Scale of Relative Perceived Distortion
Statistical Analysis
S1
S2
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0
Grid DotsHatching Paper NoisePaintPigmentsRegular
patterns
Irregular
patterns
Cross-
hatching
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0 1.5
GridDots Hatching Paper NoisePaint PigmentsNear-regular
patterns
Irregular
patterns
Cross-
hatching
Paper NoisePaintPigments
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
Overall contrast of patterns
Feature shapes
October 2, 2009Quality Assessment of Fractilized Textures 25
Interval Scale of Relative Perceived Distortion
Statistical Analysis
S1
S2
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0
Grid DotsHatching Paper NoisePaintPigmentsRegular
patterns
Irregular
patterns
Cross-
hatching
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0 1.5
GridDots Hatching Paper NoisePaint PigmentsNear-regular
patterns
Irregular
patterns
Cross-
hatching
Irregular patterns Cross-hatchingDotsHatching
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
Overall contrast of patterns
Feature shapes
October 2, 2009Quality Assessment of Fractilized Textures 26
Interval Scale of Relative Perceived Distortion
Statistical Analysis
S1
S2
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0
Grid DotsHatching Paper NoisePaintPigmentsRegular
patterns
Irregular
patterns
Cross-
hatching
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0 1.5
GridDots Hatching Paper NoisePaint PigmentsNear-regular
patterns
Irregular
patterns
Cross-
hatching
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
Quite similar frequencies
October 2, 2009Quality Assessment of Fractilized Textures 27
Ranking Criteria
Statistical Analysis
0%
5%
10%
15%
20%
25%
30%
35%
40%
contrast
sharpness
scale
other
empty
S1 S2
Fre
qu
en
cy a
t w
hic
h e
ach
cri
teri
on
has b
een
used
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
contrast
sharpness
scale
others
empty
Quite similar frequencies
• Irregular preferences for different textures
October 2, 2009Quality Assessment of Fractilized Textures 28
Ranking Criteria
Statistical Analysis
0%
10%
20%
30%
40%
50%
60%
S2S1
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
Quite similar frequencies
• Irregular preferences for different textures
• Top 3 additional criteria proposed by the participants:
Pattern coherence
Density
Shape
October 2, 2009Quality Assessment of Fractilized Textures 29
Ranking Criteria
Statistical Analysis
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
Previous Work
Experimental Framework
Statistical Analysis
Correlation with Objective Metrics
Image Quality Metric / Global Image Statistic
Local Image Statistic
October 2, 2009Quality Assessment of Fractilized Textures 30
Outline
Correlation with Objective Metrics
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• 11 quality assessment metrics MetrixMux Matlab© package by Matthew Gaubatz
(http://foulard.ece.cornell.edu/gaubatz/metrix_mux/)
No significant correlation distortion too strong
• 3 global statistics
Inconclusive results consider simultaneously contrast, sharpness and scale
October 2, 2009Quality Assessment of Fractilized Textures 31
Image Quality Metrics / Global Image Statistic
Correlation with Objective Metrics
peak signal-to-noise ratio (PSNR)
signal-to noise ratio (SNR)
structural similarity index (SSIM)
multi-scale SSIM index (MSSIM)
visual signal-to-noise ratio (VSNR)
visual information fidelity (VIF)
pixel-based VIF (VIFP)
information fidelity criterion (IFC)
universal quality index (UIQ)
noise quality measure (NQM)
weighted signal-to-noise ratio (WSNR)
Histograms
Power spectra
Distribution of contrast [BG93]
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Gray level co-occurrence matrix (GLCM) [HSD73]
Texture descriptor [TJ93]
Local image property
Match certain levels of human perception [JGSF76]
Linked to density and pattern coherence criteria
Parameters selection
• Average Co-occurrence Error [CRT01]
High correlation with the perceptual interval scale(Person’s correlation: 0.953 for S1 and 0.836 for S2 )
October 2, 2009Quality Assessment of Fractilized Textures 32
Local Image Statistic
Correlation with Objective Metrics
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
ACE relevant estimator of the distortion
October 2, 2009Quality Assessment of Fractilized Textures 33
Interval Scale of Relative Perceived Distortion
S1
S2
Correlation with Objective Metrics
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0
Grid DotsHatching Paper NoisePaintPigmentsRegular
patterns
Irregular
patterns
Cross-
hatching
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0 1.5
GridDots Hatching Paper NoisePaint PigmentsNear-regular
patterns
Irregular
patterns
Cross-
hatching
AC
E
1.2
1.0
0.8
0.6
0.4
AC
E
1.4
1.2
1.0
0.8
0.6
r² = 0.6992
r² = 0.9075
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• First step toward the evaluation of texture-based NPR techniques
10 classes of NPR medium
User-study framework
Dataset and analysis methodology
Quality assessment metric: ACE
• Future work:
Other texture or vision descriptors
Dynamic version of the fractalization process
Trade-off between temporal continuity and texture dissimilarity
October 2, 2009Quality Assessment of Fractilized Textures 34
Conclusions
Conclusions
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Project web page
http://artis.inrialpes.fr/~Pierre.Benard/TextureQualityMetric/
Dynamic web interface
Full-size figures
R scripts
• Acknowledgments
All the participants of the study
Jean-Dominique Gascuel, Olivier Martin, Fabrice Neyret, Pierre-ÉdouardLandes, Pascal Barla, Alexandrina Orzan and the anonymous reviewers
October 2, 2009Quality Assessment of Fractilized Textures 35
Thank you for your attention
Conclusions
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Proportion of each pair:
• Conversion to z-Scores:
with the mean and the standard deviation of these proportions
• Empirically verified
Normal Q-Q plots
Shapiro-Wilk test
Better confidencefor S2 than S1
October 2, 2009Quality Assessment of Fractilized Textures 36
Thurstone’s law of comparative judgement
Normal distribution assumption
S1 S2
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Wilcoxon rank sum test
Non-parametric test
Assess if two independent samples of observations come from the same distribution
No assumption about this distribution
Null hypothesis H0:
“the two considered samples are drawn from a single population”
Group pairs for which H0 cannot be rejected
October 2, 2009Quality Assessment of Fractilized Textures 37
Wilcoxon rank sum test (Mann-Witney U test)
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
Overall contrast of patterns
Feature shapes
October 2, 2009Quality Assessment of Fractilized Textures 38
Interval Scale of Relative Perceived Distortion
Statistical Analysis
S1
S2
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0
Grid DotsHatching Paper NoisePaintPigmentsRegular
patterns
Irregular
patterns
Cross-
hatching
-1.5
Z-Scores
-1.0 -0.5 0.0 0.5 1.0 1.5
GridDots Hatching Paper NoisePaint PigmentsNear-regular
patterns
Irregular
patterns
Cross-
hatching
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
contrast
sharpness
scale
others
empty
Quite similar frequencies
• Irregular preferences for different textures
October 2, 2009Quality Assessment of Fractilized Textures 39
Ranking Criteria
Statistical Analysis
0%
10%
20%
30%
40%
50%
60%
S2S1
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Proposed criteria:
• Additional criteria proposed by participants:
October 2, 2009Quality Assessment of Fractilized Textures 40
Ranking Criteria
Statistical Analysis
contrast sharpness scale other empty
S1 21.96% 26.86% 24.83% 14.4% 8.95%
S2 28.27% 35.21% 21.72% 7.12% 7.07%
density 15%
shape 10%
pattern coherence 21%
frequency 4%
relief 2%
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Gray Level Co-occurrence Matrices
n matrices of size G x G
n = number of displacement vectors
G = gray-level quantization step
= number of occurrence of gray-level pair
a distance d apart
October 2, 2009Quality Assessment of Fractilized Textures 41
Local Image Statistic
Correlation with Objective Metrics
G
G
11
1
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Gray Level Co-occurrence Matrices
n matrices of size G x G
n = number of displacement vectors
G = gray-level quantization step
= number of occurrence of gray-level pair
a distance d apart
October 2, 2009Quality Assessment of Fractilized Textures 42
Local Image Statistic
Correlation with Objective Metrics
G
G
11
1
1
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA)
• Average Co-occurrence Error [CRT01]
Distance between 2 sets of GLCM
October 2, 2009Quality Assessment of Fractilized Textures 43
Local Image Statistic
Correlation with Objective Metrics
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA) October 2, 2009Quality Assessment of Fractilized Textures 44
References I
[BBT09] Pierre Bénard, Adrien Bousseau, and Joëlle Thollot, Dynamic solid textures for real-time coherent stylization, ACM SIGGRAPH Symposium on Interactive 3D Graphics and Game, 2009.
[BG93] Rosario M Balboa and Norberto M Grzywacz, Power spectra and distribution of contrasts of natural images from different habitats, Vision Research (1993).
[BSM+07] Simon Breslav, Karol Szerszen, Lee Markosian, Pascal Barla, and Joëlle Thollot, Dynamic 2D patterns for shading 3D scenes, SIGGRAPH 07: ACM Transactions on Graphics (2007).
[CRT01] A.C. Copeland, G. Ravichandran, and M.M. Trivedi, Texture synthesis using gray-level co-occurrence models, algorithms, experimental analysis and psychophysical support, Optical Engineering (2001).
[CTP+03] Matthieu Cunzi, Joëlle Thollot, Sylvain Paris, Gilles Debunne, Jean-Dominique Gascuel, and Frédo Durand, Dynamic canvas for immersive non-photorealistic walkthroughs, Proceedings of Graphics Interface, 2003.
[CWNA08] Martin Cadík, Michael Wimmer, Laszlo Neumann, and Alessandro Artusi, Evaluation of HDR tone mapping methods using essential perceptual attributes, Computers & Graphics (2008).
[GRG04] Bruce Gooch, Erik Reinhard, and Amy Gooch, Human facial illustrations: Creation and psychophysical evaluation, ACM Trans. Graph. 23 (2004), no. 1, 27–44.
[HSD73] Robert M. Haralick, K. Shanmugam, and Its’Hak Dinstein, Textural features for image classification, Systems, Man and Cybernetics, IEEE Transactions on 3 (1973), no. 6, 610–621.
[INC+06] Tobias Isenberg, Petra Neumann, Sheelagh Carpendale, Mario Costa Sousa, and Joaquim A. Jorge, Non-photorealistic rendering in context: an observational study, NPAR ’06: Symposium on Non-photorealistic animation and rendering, ACM, 2006.
[JGSF76] B. Julesz, E. N. Gilbert, L. A. Shepp, and H. L. Frisch, Inability of humans to discriminate between visual textures that agree in second-order statistics –revisited, Perception (1976).
[Ken75] M. G. Kendall, Rank correlation methods, Hafner Publishing Company, Inc, 1975.
Bénard – Thollot – Sillion (LJK - INRIA) /32Bénard – Thollot – Sillion (LJK - INRIA) October 2, 2009Quality Assessment of Fractilized Textures 45
References II
[KLK+00] Allison W. Klein, Wilmot W. Li, Michael M. Kazhdan, Wagner T. Correa, Adam Finkelstein, and Thomas A. Funkhouser, Non-photorealistic virtual environments, Proceedings of SIGGRAPH 2001, ACM, 2000.
[LCTS05] Patrick Ledda, Alan Chalmers, Tom Troscianko, and Helge Seetzen, Evaluation of tone mapping operators using a high dynamic range display, SIGGRAPH 05 : ACM Transactions on Graphics (2005).
[MIA+08] Ross Maciejewski, Tobias Isenberg, William M. Andrews, David S. Ebert, Mario Costa Sousa, and Wei Chen, Measuringstipple aesthetics in hand-drawn and computer-generated images, IEEE Comput. Graph. Appl. (2008).
[SD04] Anthony Santella and Doug DeCarlo, Visual interest and NPR: an evaluation and manifesto, NPAR ’04: Symposium on Non-photorealistic animation and rendering, ACM, 2004.
[SFWG04] William A. Stokes, James A. Ferwerda, Bruce Walter, and Donald P. Greenberg, Perceptual illumination components: a new approach to efficient, high quality global illumination rendering, ACM Transactions on Graphics (2004).
[SSB06] H.R. Sheikh, M.F. Sabir, and A.C. Bovik, A statistical evaluation of recent full reference image quality assessmentalgorithms, IEEE Transactions on Image Processing (2006).
[SSLR96] Jutta Schumann, Thomas Strothotte, Stefan Laser, and Andreas Raab, Assessing the effect of non-photorealistic rendered images in cad, CHI ’96: Proceedings of the SIGCHI conference on Human factors in computing systems, ACM, 1996.
[TJ93] Mihran Tuceryan and Anil K. Jain, Texture analysis, The Handbook of pattern recognition & computer vision (1993).
[Tor58] W. S. Torgerson, Theory and methods of scaling, Wiley, 1958.
[Win05] Stefan Winkler, Perceptual video quality metrics – a review, Digital Video Image Quality and Perceptual Coding, CRC Press, 2005.