do-it-yourself eye tracker: how wide viewing angle should...

Do-It-Yourself Eye Tracker: How Wide Viewing Angle Should theEye Tracking Cover?

Michal Kowalik∗

Supervised by: Radoslaw Mantiuk†

Faculty of Computer ScienceWest Pomeranian University of Technology in Szczecin

Poland

Abstract

In the paper we research the relations between the eyetracker accuracy and the human view angle. We measurethe accuracy of the gaze point estimation for a typical andwide view angles and discuss limits of the field of viewcovered by an eye tracker. The measurements are capturedduring perceptual experiments with human observers. Webuilt our own construction of eye tracker based on thepupil-detection technique. We used this eye tracker, calledDo-It-Yourself, in the experimental hardware setup.

Keywords: eye tracking,eye tracker hardware,view angleestimation,subjective experiments

1 Introduction

Eye tracking devices determine the position of the eye inspace and compute position of a gaze point and a gazedirection. This information is utilised in science and tech-nology, e.g. to test peoples’ preferences concerning adver-tisement, or to control computer via the eye tracker inter-face, etc.

The progress in technology increases availability ofcomputer monitors with large diagonals. They cover widerviewing angle and strengthen impression of the visualisa-tion realism. Most probably, we can expect a display thatcovers the whole 180◦ degrees of human visual angle inthe near future. The eye tracking technology must be ad-justed to these parameters. However, other limitations ofHuman Visual System (HVS), like foveal vision, also in-fluence the eye tracker operation.

The main objective of the project is to determine howwide viewing angle should cover eye tracker. In the paperwe measure accuracy of eye tracker for small and largeview angles. We determine the limits of accuracy resultingfrom eye tracker hardware design and possibilities of gazeestimation algorithms.

We conduct perceptual experiments to measure eyetracker accuracy for a number of observers and for increas-

∗[email protected]†[email protected]

ing view angles. The hardware setup used during experi-ments is based on the Do-It-Yourself (DIY) eye tracker.We built this low cost eye tracker to gain full control overthe eye tracking pipeline. The DIY eye tracker is con-trolled by the open source software available in Internet.

In Section 2 presents basic terminology and classifica-tion of eye tracking techniques. The DIY eye tracker con-struction is depicted in Section 3. In Section 4 we presentalgorithms used for the gaze point computation and definethe eye tracker accuracy concept. In Section 5 experimen-tal procedure is described together with the results discus-sion. We conclude in Section 6.

2 Background and previous works

The tracking of viewing direction is known in science formany years. With eye tracking techniques we are able toidentify the place which a man is looking at. This disci-pline deals with the measurement, recording and analyz-ing data about the location and movements of the eyeballs.The results of the eye tracker work is the point of regard.A subset of the points of regard is known as an area of in-terest (region of interest, ROI). Science knows eye track-ing analog methods for example contact lenses [13] orelectro-oculogram [1]. These methods are invasive andcome into a strong interaction with the user. Modern eyetracking systems use the image of eye obtained by videoequipment to calculate the point of regard. They are muchmore comfortable for participants than the analogue meth-ods. We distinguish two main approaches in the designingprocess of video based eye-tracking systems [6, 5]: mo-bile - the camera is mounted on the head or remote - thecamera is located near the monitor. An example of a re-mote system consists of a camera placed centrally underthe monitor and infrared sources. The mobile system con-sists of glasses or a helmet on users head with mountedcameras that will record the movements of an eye.

Eye tracking systems are divided into working on theeye images grabbed in visible light [10] or infrared light,based on the image of one eye [15] or stereoscopic vision[4].The infra-red eye apparition allows to use three charac-teristic occurrences: the effect of the dark pupil, the effect

Proceedings of CESCG 2011: The 15th Central European Seminar on Computer Graphics (non-peer-reviewed)

of the bright pupil and the corneal reflection. In the firstcase, the pupil of the eye looks like a dark disk surroundedby a bright ring. In the second case the pupil is bright. Thecorneal reflection is a flash located on the surface of theeye. [6]

Figure 1: Appearance of human eye in infrared light:A) dark pupil and corneal reflection, B) bright pupil.

The changes analysis of the vector connecting the centreof the pupil and corneal reflection is a classic example ofthe remote eye tracking method. Assuming that the eye isa sphere and rotates around its own centre and camera withinfrared source is stationary then a corneal reflection po-sition is unchanged. Also corneal reflection (CR) stays inthe same position regardless of the rotation of the eyeball.In this case corneal reflection can be used as a referencepoint. The centre of the pupil (or iris) with a corneal re-flection create a vector which is mapped to the coordinatesof the screen during the calibration process(estimation ofgaze point). This solution is non-invasive and allows userto small head movements. [12]. The remote methods di-vide into: based on changes of the pupil - eye corner vector[19], mapping of four corneal reflections [17, 18, 7] andbased on the three-dimensional model of the eye [15].

Tracking pupil centre is a method used in mobile eyetrackers (mounted on the head). It uses dark pupil, thresh-olding and model fitting method. The position of pupilcentre is compensated with parameters derived in the cal-ibration process. The result is an estimated point of gaze[11, 16]. The algorithms which works in the visible lightuse the centre of the iris to calculate regard point.

The mobile eye tracking systems are less comfortablein use than the remote systems. Their advantage is thatwith proper implementation and hardware configurationthey are not limited only to test items on the screen butallow us to operate in the real world.

3 Do-it-yourself Eye Tracker

In our project was created a Do-it-yourself Eye Trackerstation (DIY ET). The main goal of the project was to cre-ate inexpensive and simply in construction eye trackingtool. DIY ET base on self constructed eye gaze trackingglasses supported by open source eye tracking application.DIY ET belongs to the group of head mounted eye track-ers. It works in infra-red spectrum using dark pupil ef-fects. The point of gaze is calculated by the position ofpupil centre.

Figure 2: DIY Eye Tracking setup.

DIY ET consists of two main parts: eye tracking glassesand computer with ITU Gaze Tracker software. The con-struction of the eye gaze tracking glasses was based onarticles [14, 3, 9].The glasses are made of off-the-shelfcomponent (Fig. 3).The main part of glasses is the cap-ture module. It is responsible for providing an image ofthe eye to the computer. This module was created by us-ing the Microsoft LifeCam VX-1000 and VX-6000. Wemounted a suitable filter in camera lens that allows cap-turing images in infrared light. The glasses are connectedto a computer via USB port. Based on the USB techni-cal specification a infra-red illumination system was inte-grated with the capture module. The infra-red LEDs arelocated on the capture module and supplied by USB ca-ble. This solution is very practical. The glasses provide apicture of an eye to the computer. Then supported applica-tion computes the point of gaze and returns it in the formof coordinates (X,Y). The coordinates are stored in LOGfile or transferred directly to another application via client-server. ITU Gaze Tracker [2] is application designed in ITUniversity of Copenhagen with open source licence 1.

Figure 3: DIY eye tracker.

4 Evaluation of eye tracker accuracy

In this section we discuss accuracy of eye tracking sys-tems. The eye tracker precision is defined by degrees ofvisual angle. In main part, the tested accuracy depends

1http://www.gazegroup.org/


on working of the constructed eye tracker. Besides the eyetracker inaccuracy there are other external sources of error.

4.1 Human field of view

The whole human viewing angle is about 180◦ horizon-tally and 130◦ vertically. However, he binocular field ofvision covers only about 120◦ horizontally. Additionally,The details are read by fovea - a part of the eye located inthe middle of the macula on the retina. It is responsiblefor sharp vision in the middle of the field of view (foveavision). Fovea extends from 1◦ to 5◦ angle of human fieldof view.

An eye tracker should operate in a view field that donot force head movements. One assumes that it is notmore than 120◦ of binocular vision. For observer sittingin 50 cm distance from a screen, a display should be up to170 cm wide.

4.2 Gaze angle

The DIY eye tracker is controlled by the ITU Gaze Trackersoftware. The application estimates the gaze point by map-ping the centre of the pupil to screen coordinates usingthe parameters obtained in the calibration process. Imageof eye in infrared light is captured in consecutive frames.The pupil centre is determined and its movements are be-ing tracked.

During calibration an observer is asked to look at con-secutive target points for a few seconds. The position ofthe eye is recorded and the eye pupil centre is calculated.Correlation between calculated position of the pupil centreand known position of the target points is used to approxi-mate coefficient a0−5 and b0−5 of the polynomial:

{screenx = a0 +a1x+a2y+a3xy+a4x2 +a5y2

screeny = b0 +b1x+b2y+b3xy+b4x2 +b5y2,(1)

where (screenx,screeny) are the gaze point coordinateson the screen, (x,y) are the coordinates of the centre of thepupil [2]. The accuracy of calibration process significantlyaffects error arising during eye tracker operation.

The accuracy of eye tracker is determined by indicat-ing the differences in position between the reference pointswith known position and measure gaze points.

4.3 Error factors affecting accuracy of eyetracker

A significant error affecting the accuracy of the gaze pointestimation is the head movement. We use a chin-rest tostabilise the head and increase the DIY eye tracker accu-racy. Other solutions utilise algorithms that compensatehead movements [8] or the head trackers. The DIY eyetracker is equipped in one camera and takes image of onlyone eye. The measurement error cannot be compensated

by the data from the second eye. Another sources of er-rors encompass inaccuracies of the pupil centre extraction,variation of lighting and of shadows covering the eye.

5 Perception study

The goal of the tests was to find relation between the ac-curacy of eye tracker and the view angle of an observer.During tests we use hardware setup based on the DIY eyetracker.

5.1 Hardware setup

Our experimental setup is presented in Figure 4. It consistsof DIY eye tracker controlled via the ITU Gaze Trackersoftware (we used version 2.0 of this software). The soft-ware was activated on Acer Aspire 5930 laptop equippedwith a dual-core Intel Core 2 Duo P7350 2.0 GHz andNVIDIA GeForce 9600M GT 512MB graphics card. Thetarget points were displayed on NEC LCD 2690WUXiwith the screen dimensions 55 x 34 cm, and native res-olution 1920x1200 pixels (60Hz).

To stabilise observes’ heads, we used the chin-restadopted from the ophthalmic slit lamp. The tests were con-ducted for two distances from eyes to the screen: 50 cmand 30 cm.

Figure 4: Hardware setup used during experiments.

5.2 Participants

Eleven men with an age from 21 to 34 participated in ourexperiment. Nine participants had normal vision, two ofthem had corrected vision with lens. We asked each par-ticipant to repeated the experiment for times for each dis-tance. The whole experiment lasted less than 8 minutes.They were aware that accuracy of the eye tracker is tested,however they do not know details of the experiment.

5.3 Procedure

The participants were asked to wear the DIY eye trackerand use the chin-rest to stabilise the head. They lookedat the target points that were displayed on the monitor aswhite circles appearing in random order. The procedurewas repeated for both 50 cm and 30 cm distances by tuningposition of the chin-rest.


5.4 Results

Figure 6 presents all data collected during the test proce-dure. Location of the target points is marked by red circle,the observers’ gaze points are depicted as a blue dots. Dis-tribution of gaze points for shorter distance (higher viewangles) is more spread out and does not follow the targetpoint position very well. It results higher accuracy error ofeye tracker. Figure 5 presents box plots of average errorfor sixteen target points. The central mark (red line) indi-cates median value of the error, the edges of the box arethe 25th and 75th percentiles, the whiskers extend to themost extreme data points not considered outliers. Outliersare plotted individually as red crosses. The blue horizontalline indicates view angle error equal to one degree.

For 50cm distance from screen, average error for all tar-get points equals to 1.00deg (with standard deviation equalto 0.95deg) for horizontal direction and 0.9deg (with stan-dard deviation equal to 0.94deg) for vertical direction. Forhigher view angles (30cm distance), the errors increase to3.07deg (standard deviation 2.94deg) and 2.33deg (stan-dard deviation 2.19deg) for horizontal and vertical direc-tion respectively.

The results indicate high influence of observers’ view-ing angle on eye tracker accuracy. However, we did not no-tice this relationship for the individual target points. Thereare no regular fluctuations of the error for central and ex-treme target points.

6 Conclusions and future work

Accuracy of the DIY eye tracker is close to one degree forstandard viewing angles (up to 30 degrees). It is satisfac-tory result considering low cost of the eye tracker. How-ever, the accuracy decreases to 3 degrees for wide view an-gles what seems to be unacceptable in most applications.

For the wide view angles the eye tracker cannot detectpupil centre accurately. The extreme situation is presentedin Figure 7B where pupil was not detected by image pro-cessing software. Combination of eye tracking with headtracking seems to be the solution of this problem. In futurework we plan to build low cost head tracking device andintegrate it with the DIY eye tracker.

Figure 7: Detection of the pupil for standard (A) and wideview angle (B).

References

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[2] Javier San Agustin, Henrik Skovsgaarda, and DanWitzner Hansen John Paulin Hansen. Low-cost gazeinteraction: Ready to deliver the promises. CHI,2009. Boston, Massachusetts, USA.

[3] J. Babcock, J. Pelz, and J. Peak. The wearable eye-tracker: A tool for the study of high-level visualtasks. Proceedings of the Military Sensing SymposiaSpecialty Group on Camouflage, February 2003.

[4] Yongqin Cui and Jan M. Hondzinski. Gaze trackingaccuracy in humans: Two eyes are better than one.Neuroscience Letters, 396:257–262, 2006.

[5] A.T. Duchowski. Eye Tracking Methodology: The-ory and Practice (2nd edition. Springer, London,2007.

[6] Riad I. Hammoud. Passive Eye Monitoring - Al-gorithms, Applications and Experiments. Springer-Verlag Berlin Heidelberg, 2008.

[7] You Jin Ko, Eui Chul Lee, and Kang Ryoung Park.A robust gaze detection method by compensatingfor facial movements based on corneal specularities.Pattern Recognition Letters, (29):1474–1485, 2008.

[8] Susan M. Kolakowski and Jeff B. Pelz. Compensat-ing for eye tracker camera movement. Proceedingsof the 2006 symposium on Eye tracking research andapplications, pages 79–85, 2006. California.

[9] D. Li, J. Babcock, and D.J. Parkhurst. openeyes: Alow-cost head-mounted eye-tracking solution. Pro-ceedings of the ACM Eye Tracking Research and Ap-plications Symposium, 2006.

[10] Dongheng Li and Derrick Parkhurst. Open-sourcesoftware for real-time visible-spectrum eye tracking.Human Computer Interaction Program, Iowa StateUniversity, USA, 2006.

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[13] D.A. Robinson. A method of measuring eye move-ments using a scleral search coil in a magnetic field.IEEE Trans. Biomed. Eng., 10, 1963.

[14] Jason S.Babcock and Jeff B. Pelz. Building alightweight eyetracking headgear. Eye Tracking Re-search & Application, 2004.

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[17] D. Yoo, J. Kim, B. Lee, and M. Chung. Non contacteye gaze tracking system by mapping of corneal re-flections. Proc. of the Internat. Conf. on AutomaticFace and Gesture Recognition, pages 94–99, 2002.

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[19] J. Zhu and J. Yang. Subpixel eye gaze tracking. Proc.of the 5th IEEE International Conference on Au-tomatic Face and Gesture Recognition, pages 131–136, 2002.


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Figure 6: Position of the target-points (red circles) and measured gaze-points (blue dots). Observers’ eyes located 50 cm(top) and 30 cm (bottom) from the screen. Point positions in pixels.


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