PPT - Andrew T. Duchowski

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Transcript PPT - Andrew T. Duchowski

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 three dimensional 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 X L , X R , Y L , Y R .

 Distance =   Control distance Experimental distance

Algorithm

If (Experimental distance < Control distance) If (X L < X R )

Convergence

Else

Convergence with crossover

. else If (Experimental distance > Control distance)

Divergence

else

No difference

.

Data Analysis

Data Analysis – Experimental Group (Individual)

500

Individual Experimental Moving Averages Compared to Aggregate Control Moving Average

-1000 -1500 0 0 -500 20000 40000 60000 80000 100000 120000 Experimental Subject 1 Experimental Subject 2 Experimental Subject 3 Experimental Subject 4 Experimental Subject 5 Control

Time (milliseconds)

400 200 0 0 -200 -400 -600 -800

Data Analysis – Placebo Group (Individual)

Individual Placebo Moving Averages Compared to Aggregate Control Moving Average

20000 40000 60000 80000 100000 Placebo Subject 1 Placebo Subject 2 Placebo Subject 3 Placebo Subject 4 Placebo Subject 5 Control 120000

Time (milliseconds)

200 0 -200 -400 -600 -800 -1000 1000

Data Analysis – Experimental Group (Aggregate)

Aggregate Experimental Values Compared to Aggregate Control Values

800 600 Experimental Trendline - Polynomial (6th degree) Experimental Trendline - Polynomial (6th degree) Treatment Trendline - Moving Average (Every 255 pts) 400

20000 40000 60000 80000 100000 120000 Time (Milliseconds)

500 400 300 200 100 0 1 -100 -200 -300 -400 -500

Data Analysis – Placebo Group (Aggregate)

Aggregate Placebo Values Aggregate Compared to Control Values

Placebo Trendline - Polynomial (6th degree) Placebo Trendline - Moving Average (Every 255 pts) Control Trendline - Polynomial (6th degree)

Time (Milliseconds)

One Way Analysis of Variance (ANOVA)

Assumptions of an ANOVA  Independence  Homogeneity of Variance  Normality Levene Statistic 3.335

100 0 -100 -200 -300 -400 -500 -600 -700 1 2 3 Case Number df1 1 4 df2 8 Sig.

.105

5 6 7 8 9 10

Descriptive Statistics

 Randomly Assigned Groups  Placebo - Five Men  Experimental - Three Men, Two Women Distance N 10 Min -599.35

Max.

33.28

Mean Statistic -133.4980

Mean Std. Error 60.4466

Std. Dev.

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) Between Groups Within Groups Total Sum of Squares 94965.981

df 1 328841.610

9 Mean Square 94965.981

233875.629

8 29234.454

F 3.248

Sig.

.109

100 0 -100 -200 -300 -400 -500 -600 -700 N = COND 5 1.00

6 5 2.00

Placebo

ANOVA and Power Analysis

N Mean 5 -36.0475

Std. Deviation 86.8910

Std. Error 38.8589

95% Confidence Interval for Mean Lower Bound Upper Bound -143.9370

71.8419

Minimum -163.99

Maximum 33.28

Experimental Total 5 -230.9485

225.6521

10 -133.4980

191.1490

100.9147

60.4466

-511.1326

-270.2378

49.2355

3.2418

-599.35

-599.35

-48.72

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 800 600 -400 -600 -800 -1000 400 200 0 -200 Experimental Trendline - Polynomial (6th degree) Experimental Trendline - Polynomial (6th degree) Treatment Trendline - Moving Average (Every 255 pts)

20000 40000 60000 80000 100000 120000 Time (Milliseconds)

500 400 300 200 -200 -300 -400 -500 100 0 1 -100

Placebo Group (Aggregate)

Aggregate Placebo Values Aggregate Compared to Control Values

Placebo Trendline - Polynomial (6th degree) Placebo Trendline - Moving Average (Every 255 pts) Control Trendline - Polynomial (6th degree)

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-Dot Stereograms. 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