wearable eye tracker

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Wearable Eye Tracker. Xiaoyong Ye Franz Alexander Van Horenbeke David Abbott. Index. Introduction Background Hardware Software System Design Algorithm Pupil Localization Ellipse Fitting Calibration Homographic Mapping Experimental Results Future Work. Introduction. - PowerPoint PPT Presentation

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SPEECH ENHANCEMENT

Wearable Eye TrackerXiaoyong YeFranz Alexander Van HorenbekeDavid Abbott

IndexIntroductionBackgroundHardwareSoftwareSystem DesignAlgorithmPupil LocalizationEllipse FittingCalibrationHomographic MappingExperimental ResultsFuture Work

IntroductionA complete system able to track the users eye and map the position of their pupil with the area at which they are looking at in the scene in front of them

BackgroundWearable Eye-Tracking informationWho has done previous workWhat they have used

Recent Methods used with eye tracker

ObjectivesHardwareWearableLow-CostLight and ConfortableMoveable eye-camera

SoftwareReal-TimeAccurateHardwareHead-Mounted GearTwo Cameras:Scene CameraEye Camera

HardwareScene CameraCaptures the scene in front of the userFixed to the head

Eye CameraCaptures the eyeWith 5 DOF with respect to the head

System DesignEye ImageScene ImagePupil LocalizationEllipse FittingCalibration Done?MappingMarker DetectionCalculate HomographyNoYesEllipse CenterPupil LocalizationAutomatic Threshold (Modified Otsus Method)

Image Morphology(Dilation, Erosion)

Connected Components Analysis(Find Pupil)

Pupil Center Estimation

Histogram of an Eye Image

GraylevelPupilBackgroundThreshold

Pupil Localization

ThresholdErosionConnect ComponentsPupil DetectionDilationFill holesEllipse Fitting1. Updating the pupil Center

2. Need 5 points for Fitting Ellipse model

3. RANSAC to deal with noisy points

Ellipse FittingRANSAC method

Edge ImageStarburst AlgorithmFeature PointsRANSACEllipse FittingCalibrationRelationship between Ellipse center to Scene Image

*

=Scene PositionHomographyPupil CenterSolving for homographies8 degrees of freedom in 3 x 3 matrix H, so at least n = 8 pairs of points are sufficient to determine it

Set up a system of linear equations:Ah = 0 where vector of unknowns h = [a,b,c,d,e,f,g,h]T

Need at least 8 eqs, but the more the better

Solve for h. solve using least-squares

X = Hx

calibration method

1. Look at Scene Marker and Press corresponding number on keyboard,

2. Each marker press 2 to 3 times.

3. Randomly select 8 pairs of points to calculate Homography.(Repeatly)

3. Choose the best Homography matrix.

Mapping

(x1, y1)(x2, y2)

Experimental ResultsFrame rate 25/second

Accurate Pupil Ellipse

Mapping error is low( 13 pixels in 640*480 image)DemoLinkhttp://www.youtube.com/watch?v=lBXLpsXBGOA&context=C25ea4ADOEgsToPDskIo6A6rLXR8eySvaEf82q6hFuture WorkHardwareLighter camerasScene camera position

SoftwareUse corneal refletionTry different mapping techniquesThank you!

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