Eye Tracking With
Stereoscopic Images
Eamon Moore, Punit Seth, Dhaval Shah
Clemson University
Introduction


Stereoscopic image – optical illusion of
depth seen by focusing ones eyes in front
of or behind an image [7]
Each eye views an image differently which
gives the perception of depth.
Eye Tracking


Eye Trackers – Can be used to track eye
movements and gaze coordinates
Gaze coordinates – Helps in understanding
why some people see stereo images and
some do not
Divergence and
Convergence



Divergence and Convergence – the
methods that people use to view
stereograms
Divergence – Moving your eyes outward in
the opposite direction
Convergence – Moving your eyes inward
Why Use Stereograms?


Marketers and researchers – Attempts are
being made to utilize ones ability to see
three-dimensional images and use them in
advertising.
Stereograms can enhance vividness,
clarity, realism, and depth.
The Experiment

Analyzing the behavior of the eyes to view
stereograms [dependant variable]



Convergence
Divergence
Looking for significant differences in
Placebo and Experimental group
[independent variable]
Hypothesis


Null Hypothesis – There will be no
significant change in the distance of the
eyes when viewing stereograms,
regardless of experimental condition.
Alternate Hypothesis – There will be
significant results that indicate divergence
of the eyes in both conditions.
Background

Brain processing – The brain
accepts two images that are
seen by each eye and creates
a completely different threedimensional picture called
stereo [6].
Figure 1: Image processing

Stereo allows you to see objects as solids
in dimension of width, height, and depth.
When Stereoscopy Started


Idea of stereoscopy preceded photography
Paintings were made by Giovanni Porta in
the late 1500s by placing images side by
side. This showed his understanding of
binocular vision.
Three-Dimensional Glasses

Three-Dimensional Glasses – red filter for
left eye, blue filter for right eye [11]
Figure 2: Red-blue Stereo Image

When looked at images that have depth, a
three-dimensional image could be seen.
Modern Stereogram

First modern stereogram created in 1959 by
Julesz [11]



Original image viewed by left eye
Modified version of original image viewed by right eye
Brain fuses both images creating the final image
Figure 3: Modern Stereogram
Single Image Stereogram


Created in 1979 by a student of Julesz, Tyler
Found that the offset idea could be applied to a
single image to create a black and white
random dot stereogram
Figure 4: Single Image stereogram
Colored Stereogram
Program


In 1991 Smith improved on the research
of Julesz by creating stereogram modeling
software.
Eliminated the need for dots and provided
color
Tracking of Eye Movements
and Visual Attention


Study conducted by Neuroinformatics Group,
Bielefield University [8]
Concentrated on vergence eye movements using
stereograms similar to the ones used in this
experiment
Figure 5: Coarse Granularity Image (left) ; Stereogram (right)
Neuroscience Institute



Gave insight about vergence eye movements
Discussed dynamics of horizontal and vertical
vergence
Study indicated that horizontal eye movements
were of more importance.
Program to Create
Stereograms

School of Electrical and Electronic
Engineering at the University of Nottingham
[3]

Created program that produces stereograms

Examined how stereograms were viewed
Experimental Design
Apparatus

Tobii Eye Tracker [16] – Video-based combined pupil and
corneal reflection eye tracker

2.4 GHz

256 MB RAM

Windows XP
Red Hat Linux Release 9,
Version 2.4.20

Sampling Rate = 50 Hz

Accuracy = 1º visual angle
Figure 6: Tobii System
Experimental Design

Between subjects

Two conditions :



Experimental group – Stereogram
Placebo group – Nonstereo Image
10 Participants
Stimulus - Control Image
Stimulus - Stereogram
The Hidden Image
Stimulus – Nonstereo Image
Salient Features

Reduced calibration points

An organized file structure

Validity = 0

Timer

Shortcut keys

Analysis option
Algorithm

Record XL, XR, YL, YR.

Distance =


Control distance
Experimental distance
Algorithm
If (Experimental distance < Control distance)
If (XL < XR)
Convergence
Else Convergence with crossover.
else If (Experimental distance > Control distance)
Divergence
else No difference.
Data Analysis
Data Analysis – Experimental
Group (Individual)
Individual Experimental Moving Averages Compared to Aggregate Control Moving Average
500
0
Distance (pixels)
0
20000
40000
60000
-500
-1000
Experimental Subject 1
Experimental Subject 2
Experimental Subject 3
Experimental Subject 4
Experimental Subject 5
Control
-1500
Time (milliseconds)
80000
100000
120000
Data Analysis – Placebo
Group (Individual)
Individual Placebo Moving Averages Compared to Aggregate Control Moving Average
400
200
0
Distance (pixels)
0
20000
40000
60000
80000
100000
-200
Placebo Subject 1
Placebo Subject 2
Placebo Subject 3
Placebo Subject 4
Placebo Subject 5
Control
-400
-600
-800
Time (milliseconds)
120000
Data Analysis – Experimental
Group (Aggregate)
Aggregate Experimental Values Compared to Aggregate Control Values
1000
800
Experimental Trendline - Polynomial (6th degree)
600
Experimental Trendline - Polynomial (6th degree)
Treatment Trendline - Moving Average (Every 255 pts)
200
-400
-600
-800
-1000
Time (Milliseconds)
1E+05
89161
100000
71904
52670
37362
7964
22853
95038
80000
80465
66056
51639
36938
22221
60000
7794
1E+05
98213
83385
68713
54164
40000
39636
24647
10158
1E+05
85698
1E+05
20000
71268
56778
42348
27081
12589
-200
14583
0
136.3
Distance (Pixels)
400
120000
Data Analysis – Placebo
Group (Aggregate)
Aggregate Placebo Values Aggregate Compared to Control Values
500
400
Placebo Trendline - Polynomial (6th degree)
Placebo Trendline - Moving Average (Every 255 pts)
300
Control Trendline - Polynomial (6th degree)
Distance (Pixels)
200
100
0
1
100000
1336 267120000
4006 5341 667640000
8011 9346 1068160000
12016 13351 1468680000
16021 17356 18691 20026
21361 22696 24031120000
25366 26701
-100
-200
-300
-400
-500
Time (Milliseconds)
One Way Analysis of Variance
(ANOVA)
Assumptions of an ANOVA
 Independence
Levene
Statistic
df1
df2
Sig.
3.335
1
8
.105
100
0
 Homogeneity of Variance
-100
-200
 Normality
Value DISTANCE
-300
-400
-500
-600
-700
1
2
3
Case Number
4
5
6
7
8
9
10
Descriptive Statistics
 Randomly Assigned Groups
 Placebo
- Five Men
 Experimental
- Three Men, Two Women
Distance
N
Min
Max.
Mean
Statistic
Mean
Std. Error
Std.
Dev.
10
-599.35
33.28
-133.4980
60.4466
191.1490
Variance
36537.957
ANOVA
• Not a significant difference between the Placebo (M = -36.048,
S = 86.891) and Experimental Group (M = -230.949,S = 225.562)
100
0
Sum of
Squares
df
Mean
Square
F
Sig.
Between
Groups
94965.981
1
94965.981
3.248
.109
Within
Groups
233875.629
Total
328841.610
-100
-200
-300
9
29234.454
-400
DISTANCE
8
-500
6
-600
-700
N=
COND
5
5
1.00
2.00
ANOVA and Power Analysis
N
Mean
Std.
Deviation
Std. Error
95% Confidence Interval for
Mean
Lower Bound
Upper
Bound
Minimum
Maximum
Placebo
5
-36.0475
86.8910
38.8589
-143.9370
71.8419
-163.99
33.28
Experimental
5
-230.9485
225.6521
100.9147
-511.1326
49.2355
-599.35
-48.72
Total
10
-133.4980
191.1490
60.4466
-270.2378
3.2418
-599.35
33.28
• Post Hoc G-Power Analysis
-power of .1077 indicates approximately 11 percent chance
that the null hypothesis could have been rejected.
Discussion
Discussion
• Stereograms
are viewed by using
convergence regardless of stimuli.
• No significant results
• Experimental group shows trend towards
divergence near the end.
• Placebo group shows a lesser trend
towards convergence
Experimental Group
(Aggregate)
Aggregate Experimental Values Compared to Aggregate Control Values
1000
800
Experimental Trendline - Polynomial (6th degree)
600
Experimental Trendline - Polynomial (6th degree)
Treatment Trendline - Moving Average (Every 255 pts)
200
-400
-600
-800
-1000
Time (Milliseconds)
89161
1E+05
100000
71904
52670
37362
22853
7964
95038
80000
80465
66056
51639
36938
22221
60000
7794
98213
1E+05
83385
68713
54164
40000
39636
24647
10158
1E+05
1E+05
85698
20000
71268
56778
42348
27081
12589
-200
14583
0
136.3
Distance (Pixels)
400
120000
Placebo Group
(Aggregate)
Aggregate Placebo Values Aggregate Compared to Control Values
500
400
Placebo Trendline - Polynomial (6th degree)
Placebo Trendline - Moving Average (Every 255 pts)
300
Control Trendline - Polynomial (6th degree)
Distance (Pixels)
200
100
0
1
100000
1336 267120000
4006 5341 667640000
8011 9346 1068160000
12016 13351 1468680000
16021 17356 18691 20026
21361 22696 24031120000
25366 26701
-100
-200
-300
-400
-500
Time (Milliseconds)
Limitations
• Low
Power
- Priori Power Analysis
• Tobii Eye Tracker
• Stereograms are harder to view on a
computer screen.
Future Work



Larger sample size
Introduce Z coordinate for the distance
from the screen
Measure characteristics such as the
diameter of the pupil while studying its
behavior.
Conclusion



Our hypothesis was incorrect; however, we were
correct in believing both groups would behave
similarly.
Stereograms are viewed by converging ones eyes;
however, a higher power study may prove
otherwise.
More research can now be conducted to
understand how stereograms can be used for
advertising, marketing, and other practical
applications.
Acknowledgements

Dr. Andrew Duchowski, PhD.,
Associate Professor, Clemson University.

Ms. Puja Seth, M.A.
Doctoral Student, University of Georgia

Mr. Jacob Hicks
Undergraduate Student, Clemson University.
References
[1] Academy of Marketing Science Review. Three-Dimensional Stereographic Visual displays in Marketing and
Consumer Research. Available at: http://www.vancouver.wsu.edu/amsrev/theory/holbrook11- 97t.htm.
Last Accessed: 10 October, 2004.
[2] Annals of the New York Academy of Sciences 2002. Binocular Eye Movement Responses to Dichoptically
Presented Horizontal and/or Vertical Stimulus Steps. Available at:
http://www.annalsnyas.org/cgi/content/full/956/1/487. Last Accessed: December 2, 2004.
[3] BBC, Nottingham. SIRDS: An optical illusion.
Available at: http://www.bbc.co.uk/nottingham/features/2003/08/sirds.shtml#what
Last Accessed: December 2, 2004.
[4] CIT,Cornell University. How To See A Magic Eye Poster.
Available At:
http://instruct1.cit.cornell.edu/courses/psych470/To_Be_Edited/How%20To%20See%20A%20Magic%20Eye%20P
oster%20(MVW).doc. Last Accessed: December 2, 2004.
[5] C. Rashbass & G. Westheimer J. Physiol. Disjunctive Eye Movements. 159, 339-360, 1961
[6] Cooper, Rachel. What is Stereo Vision?. 2004. Available At: http://www.vision3d.com/stereo.html.
Last Accessed:16 September 2004.
[7] Dictionary.com. Available at: http://dictionary.reference.com/search?q=stereogram
Last Accessed: December 2, 2004.
[8] Essig, Kai and Ritter, Helg. Tracking of Eye Movements and Visual Attention.
Available at: http://www.techfak.uni-bielefeld.de/ags/ni/projects/eyetrack/eye_autostereo.html.
The Neuroinformatics Group. Bielefeld University. Last Accessed: 10 October, 2004.
References
[9] Faul, F., & Erdfelder, E. (1992). G-Power: A priori, post- hoc, and compromise power analyses for MS-DOS
(computer program). Bonn, FRG:Bonn University, Department of Psychology.
[10] History of Photography and the Camera.
Available At: http://inventors.about.com/library/inventors/blphotography.htm
Last Accessed: December 2, 2004.
[11] Magic Eye Inc®. Frequently Asked Questions. 2004.
Available at: http://magiceye.com/faq.htm. Last Accessed: 16 September 2004.
[12] Mowforth, P. et al. Vergence Eye Movements Made in Response to Spatial-Frequency-Filtered Random-DotStereograms. Perception, 10, 299-304, 1981
[13] Patrick Hahn. The History of Stereograms 1996.
Available At:http://www2.vo.lu/homepages/phahn/rds/history.htm. Last Accessed: December 2, 2004.
[14] Robert Leggat. Stereoscopic photography 2003.
Available At: http://www.rleggat.com/photohistory/history/stereosc.htm.
Last Accessed: December 2, 2004.
[15] Sandin, Daniel et al. The VarrierTM Auto-Stereographic
Display. Available at http://www.evl.uic.edu/todd/varrier/VarrierSPIE.html.
Electronic Visualization Laboratory. University of Illinois at Chicago. Last Accessed: 10 October, 2004.
[16] Tobii Technology. User Manual. Available at :
http://andrewd.ces.clemson.edu/courses/cpsc412/docs/UsersManual_TobiiClearView_2_1_0.pdf
Last Accessed: December 2, 2004.
Questions