Human Visual System Models in Computer...
Transcript of Human Visual System Models in Computer...
![Page 1: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/1.jpg)
Human Visual System Models in Computer Graphics
Tunç O. Aydın MPI Informatik Computer Graphics Department
HDR and Visual Perception Group
![Page 2: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/2.jpg)
Outline Reality vs. Perception
– Why even bother modeling visual perception
The Human Visual System (HVS) – How the “wetware” affects our perception
HVS models in Computer Graphics – Visual Significance of contrast
– Contrast Detection
Our contributions – Key challenges
![Page 3: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/3.jpg)
High Low
Difference Image (Color coded)
Invisible Bits & Bytes
Reference (bmp, 616K) Compressed (jpg, 48K)
![Page 4: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/4.jpg)
Variations of Perception
No one-to-one correspondence between visual perception and reality !
“Perceived Visual Data” instead of luminance or arbitrary pixel values
![Page 5: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/5.jpg)
The Human Visual System (HVS) Experimental
Methods of Vision Science – Micro-electrode
– Radioactive Marker
– Vivisection
– Psychophysical Experimentation
![Page 6: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/6.jpg)
HVS effects (1): Glare
Video Courtesy of Tobias Ritschel
Disability Glare (blooming)
![Page 7: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/7.jpg)
Disability Glare Model of Light
Scattering
– Point Spread Function in spatial domain
– Optical Transfer Function in Fourier Domain [Deeley et al. 1991]
Spatial Frequency [cy/deg]
Mo
du
lati
on
![Page 8: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/8.jpg)
(2): Light Adaptation
Time Adaptation Level:
10-4 cd/m2 Adaptation Level:
17 cd/m2
![Page 9: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/9.jpg)
Perceptually Uniform Space Transfer function:
Maps Luminance to Just Noticeable Differences (JNDs) in Luminance. [Mantiuk et al. 2004, Aydın et al. 2008]
Res
po
nse
[JN
D]
Luminance [cd/m2]
![Page 10: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/10.jpg)
(3): Contrast Sensitivity
CSF(spatial frequency, adaptation level, temporal freq., viewing dist, …)
Co
ntr
ast
Spatial Frequency
![Page 11: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/11.jpg)
November 6, 2011
Steady-state CSFS: Returns the Sensitivity (1/Threshold contrast), given the adaptation luminance and spatial frequency [Daly 1993].
Contrast Sensitivity Function (CSF)
![Page 12: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/12.jpg)
(4): Visual Channels Cortex Transform
![Page 13: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/13.jpg)
(5): Visual Masking
Loss of sensitivity to a signal in the presence of a “similar frequency” signal “nearby”.
![Page 14: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/14.jpg)
Modeling Visual Masking Example: JPEG’s
pointwise extended masking:
C’: Normalized Contrast
![Page 15: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/15.jpg)
HVS Models in Graphics/Vision
HDR LDR
Tone Mapping Compression
Rate the
Quality
Quality Assessment Panorama Stitching
![Page 16: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/16.jpg)
Visual Significance Pipeline
kN
n
k
ref
k
tst RRR
/1
1
ˆ
![Page 17: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/17.jpg)
Contrast Detection Pipeline
Log
Thre
sho
ld E
leva
tio
n
Log Contrast Contrast Difference
Pro
bab
ility
of
Det
ecti
on
N
n
nPP1
11ˆ
![Page 18: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/18.jpg)
CONTRIBUTIONS: VISUAL SIGNIFICANCE
![Page 19: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/19.jpg)
Visually Significant Edges Key Idea: Use the
magnitude of the HVS model’s response as the measure of edge strength, instead of gradient magnitude.
Result (1): Significant improvement in application results, especially for HDR images
Result (2): Only minor improvements observed in LDR retargeting and panorama stitching.
[Aydın, Čadík, Myszkowski, Seidel. 2010 ACM TAP]
![Page 20: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/20.jpg)
Calibration Procedure
CSF from the Visible Differences Predictor [Daly’93]
JPEG’s pointwise extended masking Calibration: CSF derived for
sinusoidal stimuli, not for edges. Perceptual experiment for
measuring edge thresholds
![Page 21: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/21.jpg)
Calibration Function
Calibration function: R: Visual Significance for sinusoidal stimulus, R’: Visual Significance for edges.
Subjective Measurements
Polynomial Fit
Metric Predictions
Polynomial Fit
Ideal Metric Response
Calibrated Metric
Response
![Page 22: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/22.jpg)
Image Retargeting
![Page 23: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/23.jpg)
Visual Significance Maps
High Low
![Page 24: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/24.jpg)
Display Visibility under Dynamically Changing Illumination
Key Idea: Extending steady-state HVS models with temporal adaptation model
Result: A visibility class estimator integrated into a software that simulates illumination inside an automobile.
[Aydın, Myszkowski, Seidel. 2009 EuroGraphics]
![Page 25: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/25.jpg)
L
Background Luminance
cvi for Steady-State Adaptation Contrast vs. Intensity
(cvi): function assumes perfect adaptation
Contrast vs. Intensity and adaptation (cvia) accounts for maladaptation
L + ∆L
Threshold Luminance
CLcvi :
CLLcvia a ,:
![Page 26: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/26.jpg)
cvia for Maladaptation
cvia
cvi
![Page 27: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/27.jpg)
Adaptation over time
Low
High
Visu
al Significan
ce t = 0 t = 0.2s t = 0.4s t = 0.8s
![Page 28: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/28.jpg)
Rendering Adaptation
[Pająk, Čadík, Aydın, Myszkowski, Seidel. 2010 Electronic Imaging]
Dark Adaptation Bright Adaptation
![Page 29: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/29.jpg)
CONTRIBUTIONS: CONTRAST DETECTION
![Page 30: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/30.jpg)
Quality Assessment (IQA, VQA)
Rate the
Quality
+ Reliable - High cost
![Page 31: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/31.jpg)
Key Idea: Find a transformation from Luminance to pixel values, such that: – An increment of 1 pixel
value corresponds to 1 JND Luminance in both HDR and LDR domains.
– The pixel values in LDR domain should be close to sRGB pixel values
Result: Common LDR Quality metrics (SSIM, PSNR) extended to HDR through the PU space transformation
Perceptually Uniform Space
[Aydın, Mantiuk, Seidel. 2008 Electronic Imaging]
![Page 32: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/32.jpg)
Perceptually Uniform Space Derivation:
for i = 2 to N
Li = Li-1 + tvi(Li-1);
end for
Fit the absolute value and subject sensitivity to sRGB within CRT luminance range
![Page 33: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/33.jpg)
Key Idea: Instead of the traditional contrast difference, use distortion measures agnostic to dynamic range difference.
Result: An IQA that can meaningfully compare an LDR test image with an HDR reference image, and vice versa. Enables objective evaluation of tone mapping operators.
Dynamic Range Independent IQA
[Aydın, Mantiuk, Myszkowski, Seidel. 2008 SIGGRAPH]
![Page 34: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/34.jpg)
5x
LDR HDR Lu
min
ance
Lum
inan
ce
LDR HDR
HDR vs. LDR
![Page 35: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/35.jpg)
Problem with Visible Differences
HDR Reference LDR Test HDR-VDP
95%
75%
50%
25%
Det
ecti
on
Pro
bab
ility
Co
ntr
ast
Loss
Local Gaussian Blur
![Page 36: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/36.jpg)
Distortion Measures
Reference Test Contrast Loss
Reference Test Contrast Amplification
Reference Test Contrast Reversal
![Page 37: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/37.jpg)
Novel Applications Tone Mapping Inverse
Tone Mapping
![Page 38: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/38.jpg)
Video Quality Assessment
DRIVQM [Aydin et al. 2010] DRIVDP [Aydin et al. 2008] (frame-by-frame)
HDR Video (tone mapped for
presentation)
![Page 39: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/39.jpg)
Key Idea: Extend the Dynamic Range Independent pipeline with temporal aspects to evaluate video sequences.
Result: An objective VQM that evaluates rendering quality, temporal tone mapping and HDR compression.
Dynamic Range Independent VQA
[Aydın, Čadík, Myszkowski, Seidel. 2010 SIGGRAPH Asia]
![Page 40: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/40.jpg)
CSF: ω,ρ,La → S
– ω: temporal frequency,
– ρ: spatial frequency,
– La: adaptation level,
– S: sensitivity.
Contrast Sensitivity Function
![Page 41: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/41.jpg)
CSF: ω,ρ,La → S
– ω: temporal frequency,
– ρ: spatial frequency,
– La: adaptation level,
– S: sensitivity.
Contrast Sensitivity Function
Spatio-temporal CSFT
![Page 42: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/42.jpg)
CSF: ω,ρ,La → S
– ω: temporal frequency,
– ρ: spatial frequency,
– La: adaptation level,
– S: sensitivity.
Contrast Sensitivity Function
Steady-state CSFS
![Page 43: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/43.jpg)
( )
Contrast Sensitivity Function
=
CSF(ω,ρ,La = L) CSFT(ω,ρ,La = 100 cd/m2) f(ρ,La)
x
÷ f =
CSFS(ρ,La) CSFS(ρ,100 cd/m2)
La = 100 cd/m2
CSFT(ω,ρ)
![Page 44: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/44.jpg)
Extended Cortex Transform
Sustained and Transient Temporal Channels [Winkler 2005] Spatial
![Page 45: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/45.jpg)
Evaluation of Rendering Methods
No temporal filtering With temporal filtering [Herzog et al. 2010]
Predicted distortion map
![Page 46: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/46.jpg)
Evaluation of Rendering Qualities
High quality Low quality Predicted distortion map
![Page 47: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/47.jpg)
Evaluation of HDR Compression
Medium Compression High Compression
![Page 48: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/48.jpg)
Validation Study Noise, HDR video compression, tone mapping
“2.5D videos”
HDR-HDR, HDR-LDR, LDR-LDR
![Page 49: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/49.jpg)
Psychophysical Validation
(1) Show videos side-by-side on a HDR Display
(2) Subjects mark regions where they detect differences
[Čadík, Aydın, Myszkowski, Seidel. 2011 Electronic Imaging]
![Page 50: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/50.jpg)
Validation Study Results Stimulus DRIVQM PDM HDRVDP DRIVDP 1 0.765 -0.0147 0.591 0.488
2 0.883 0.686 0.673 0.859
3 0.843 0.886 0.0769 0.865
4 0.815 0.0205 0.211 -0.0654
5 0.844 0.565 0.803 0.689
6 0.761 -0.462 0.709 0.299
7 0.879 0.155 0.882 0.924
8 0.733 0.109 0.339 0.393
9 0.753 0.368 0.473 0.617
Average 0.809 0.257 0.528 0.563
![Page 51: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/51.jpg)
Conclusion Starting Intuition: Working on “perceived” visual data,
instead of “physical” visual data.
![Page 52: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/52.jpg)
Limitations and Future Work What about the rest of
the brain? – Visual Attention
– Prior Knowledge
– Gestalt Properties
– Free will
– …
User interaction?
Depth perception
![Page 53: Human Visual System Models in Computer Graphicszurich.disneyresearch.com/~taydin/_resources/slides/...Human Visual System Models in Computer Graphics Tunç O. Aydın MPI Informatik](https://reader031.fdocuments.net/reader031/viewer/2022030510/5ab9988d7f8b9a28468e3da9/html5/thumbnails/53.jpg)
Acknowledgements Advisors
– Karol Myszkowski, Hans Peter Seidel
Collaborators
– Martin Čadík, Rafał Mantiuk, Dawid Pająk, Makoto Okabe
AG4 Members
– Current and past
AG4 Staff
– Sabine Budde, Ellen Fries, Conny Liegl, Svetlana Borodina, Sonja Lienard.
Thesis Committee
– Phillip Slusallek, Jan Kautz, Thorsten Thormählen.
Family
– Süheyla and Vahit Aydın, Irem Dumlupınar